WO2018215590A1 - Cancer-associated venous thromboembolic events - Google Patents

Abstract

The present invention concerns the provision of an improved method for the diagnosis and prediction of thrombotic events in cancer patients, and provides additionally respective kits.

Description

Cancer-associated venous thromboembolic events

FIELD OF THE INVENTION

The present invention relates to the field of thrombotic diseases or disorders. More specifically, it relates to markers and methods for determining whether a subject, particularly a human subject, suffering or under the suspicion of suffering from cancer, is at risk of developing thromboembolic diseases or disorders, developing a thromboembolic event, having a thromboembolic disease or disorder, or is or will be experiencing a complication of a thromboembolic disease.

TECHNICAL BACKGROUND

Cancer is a major risk factor for venous thromboembolism (VTE), as well as other thromboembolic diseases, and is responsible e.g. for 18% of all cases of incident VTE¹. Across all patients with cancer, the risk for VTE is elevated 7-fold as compared to non- cancer patients, and in certain malignancies, the risk for VTE may be increased up to 17- fold². VTE is discovered in a fifth of all cancer patients and as many as half of cancer postmortem examinations³. The incidence of cancer-associated VTE is particularly high during the first months after diagnosis, if distant metastases are present, and after initiating chemotherapy^2,4,5.

Cancer-associated VTE bears several clinical and economic implications, including increased hospitalization rates and the potential for delays in cancer therapy⁶. In patients with cancer, VTE is the second leading cause of death; in fact, of every seven patients with cancer who die while hospitalised, one will die of pulmonary embolism¹, which is a typical direct consequence of VTE. Even among patients who survive an episode of VTE, complications such as recurrent VTE, post-thrombotic syndrome, and chronic thromboembolic pulmonary hypertension are common, costly, and have a profound impact on the patient^'s quality of life¹.

Due to the relevance of cancer associated-VTE, scientific societies have already published different guidelines covering the identification of cancer patients at risk, possible prevention strategies and the treatment of cancer-associated VTE^6,7,8.

A) Identification of cancer patients at risk of developing VTE

Table 1 shows the currently known thrombotic risk factors identified in patients suffering from cancer-associated VTE. Those risk factors can be divided in demographic, cancer related, treatment related, and other risk factors. Table 1.

Thrombotic risk

factors

Patient

old age

gender: higher in women than in men

ethnicity

higher in African Americans

lower in Asians

Family history of VTE

Personal history of VTE

Body mass index

Cancer

Site

brain

pancreas

kidney

stomach

lung

gynaecologic, haematologic malignances stage

advanced stage

initial period after diagnosis

Treatment

hospitalization

surgery

chemo- and hormonal therapy

anti-angiogenic therapy

erythropoiesis stimulating agents

Megestrol acetate

central vanous catheter

Other

Plaster cast immobilization

Trauma

hormonal contraceptive

pregnancy

collagen vascular diseases

heart

failure

D-dimer

Nephrotic syndrome

P-selectin In the following, additional information is provided on both cancer- and treatment related risk factors.

Cancer related risk factors

The so-called "cancer related risk factors" describe the incidence of thrombotic events, diseases or disorder, in particular of VTE, according to tumour type and stage. The rate of e.g. VTE is consistently higher in patients with cancer of the pancreas, stomach, brain, kidney, uterus, lung, prostate, leukemia or ovary⁹. Among the haematological malignancies, lymphoma, leukemia and myeloma disease were reported to have the highest rates of VTE¹⁰'¹¹.

The extent of malignant disease also affects the likelihood of developing thrombotic events, diseases or disorder, in particular of VTE. Multiple studies have shown an increased risk of VTE in patients with advanced-stage cancer⁹. An analysis of data from the California Cancer Registry between 1993 and 1995 highlighted metastatic disease as the strongest predictor of VTE and VTE complications¹². Similarly, it is known that cancer patients with distant metastases had almost a twofold increased risk of VTE compared with those without metastases.

Treatment related risk factors

Many standard anticancer treatment strategies have been shown to increase the risk of thrombotic events, diseases or disorder, in particular of VTE complications. These factors include both surgical procedures and non-surgical treatments. Another important risk factor is the presence of a central venous catheter¹³.

Surgery is a well-known risk factor for development of VTE in patients without cancer. Cancer patients undergoing surgery are at increased risk (i. e. 3- to 5-fold) for postoperative thrombosis compared to surgical patients who do not have cancer, and this risk can persist for up to seven weeks after the procedure (Am J Surg 1970; 120: 527-530). VTE is the most common cause of death 30 days after surgery in cancer patients (46%), followed by cancer progression (12%)¹⁴.

Non-surgical anticancer treatment strategies are also associated with a high incidence of thrombotic events, diseases or disorder, in particular of VTE. Active treatments including chemotherapy, adjuvant chemotherapy, hormonal therapy, antiangiogenic agents, and combination regimens all have a prothrombotic effect in cancer patients. Chemotherapy, either as primary or adjuvant therapy, significantly increases the risk of thrombotic events, diseases or disorder, in particular of VTE complications in patients with cancer. Recently, a prospective study of nearly 4500 patients receiving outpatient chemotherapy reported a 2.7-fold increase in arterial thrombosis, and a 47-fold increase in the mortality rate from VTE compared with the general population¹⁵. Hormone therapy in combination with chemotherapy enhances the incidence of VTE in women with breast cancer. Studies have reported that women who received the selective estrogen receptor modulator tamoxifen had a 1.5- to 7.1-fold increase in the risk of developing symptomatic VTE, compared with placebo or no treatment.

New therapeutic agents that inhibit angiogenesis are being developed as treatments for various solid tumours such as non-small-cell lung cancer, breast cancer, and colon cancer. Targeted antiangiogenic agents, such as bevacizumab, the monoclonal antibody to vascular endothelial growth factor, have shown efficacy in improving survival rates among patients with advanced disease. However, the addition of bevacizumab to chemotherapy regimens is associated with a high incidence of thrombotic events.

The use of recombinant human erythropoietin (EPO) and other haematopoietic growth factors, such as granulocyte-macrophage colony-stimulating factor and granulocyte-colony stimulating factor, as supportive therapy in cancer patients appears to increase the risk of VTE.

Long-term central venous catheters (CVC) have considerably improved the management of cancer patients. However, they also represent a significant risk factor for VTE.

Risk stratification

The interaction and relative effects of the risk factors associated with VTE in cancer patients is highly complex, making the pre-treatment assessment of VTE difficult. As summarized in Table 1, several demographic, cancer-associated, and treatment-related factors are known to increase the risk of thrombosis. Until recently, no clinically validated predictive models, including clinical and laboratory markers, have been developed to identify the actual risk of developing thrombotic events, diseases or disorder, in particular of VTE in these patients. However, a VTE risk assessment model for patients undergoing chemotherapy has been published by Khorana et al. based on five predictive variables in cancer patients¹⁶:

1. cancer site (very high risk: stomach and pancreas; high risk: lung, lymphoma, gynaecologic, bladder, and testicular);

2. pre-chemotherapy platelet count of >350 ^χ 109/1 = high risk;

3. haemoglobin levels < 100 g/l (or the use of erythropoiesis-stimulating agents) = high risk;

4. pre-chemotherapy leukocyte count >11 ^χ 109/1 = high risk;

5. body mass index >35kg/m² = high risk.

Scientific Societies have published guidelines recommending that patients with cancer be assessed for VTE risk at the time of chemotherapy and periodically thereafter. In outpatient setting, risk assessment can be conducted based on the above validated risk assessment tool developed by Khorana¹⁶.

B) Prophylaxis of thrombotic events, diseases or disorder, in particular of VTE

The prevention of thrombotic events, diseases or disorder, in particular of VTE in c^ er patients is of vital importance in light of the difficulties associated with the treatment of thrombotic events, diseases or disorder, in particular of VTE in these patients, as they are also prone to greater recurrence rates and a higher incidence of bleeding complications¹⁷.

It has been shown that cancer patients undergoing surgery benefit from effective pharmacological prophylaxis, and that extended-duration thromboprophylaxis with low molecular weight heparin (LMWH) may be beneficial to patients undergoing major abdominal or pelvic surgery. This is reflected in the guidelines: "All patients undergoing major cancer surgery should receive heparin-based prophylaxis for a minimum of 7-10 days, with supportive mechanical prophylaxis in those patients at highest risk" ¹⁸.

Thromboprophylaxis has been shown to decrease deep venous thrombosis (DVT) specifically in high-risk hospitalized patients.

Several randomized controlled trials of thromboprophylaxis in ambulatory cancer patients have been reported. The most recent trials, conducted in patients with advanced pancreatic cancer who receive systemic chemotherapy, have shown positive results with low molecular weight heparin (LMWH) prophylaxis. In particular, the CONKO-004 trial found 87% risk reduction of VTE using LMWH enoxaparin at 1 mg/kg body weight once daily for three months compared with no prophylaxis (9.9% vs 1.3%; p < 0.01). Recently, LMWH nadroparin was found to reduce the incidence of thromboembolic events in ambulatory cancer patients receiving chemotherapy for metastatic or locally advanced disease.

The recommendations of the various guidelines in the different clinical settings are summarized in Table 2.

recommended not recommenrfed

patients • prophylaxis- with low-dose UFH or LMWH If anticoagulation is contra- undergoing surgery for at least 7-10 days ^'indicated, consider

• extended prophylaxis up to- four weeks mechanical methods atone.

after discharge in patients with htgh.risk

features

hospitalized VTEp ^'roph laxis with anticoagulants if anticoagulation ^'is contra- patients ^'indicated

mbulatory -patients only patients with multiple myeloma otherwise, no routine^'

receiving/ receiving thalidomide or lenalidbmide- prophylaxis- chemotherapy prophylaxis with LMWH or adjusted dose^'

warfarin

C) Treatment of thrombotic events, diseases or disorder, in particular of VTE

Patients with cancer who develop a thrombotic events, diseases or disorder, in partici of VTE episode should be managed according to the guidelines. Except for selected patients requiring aggressive treatments, the large majority of cancer patients who develop thromboembolic events, diseases or disorder, in particular a VTE episode, should be treated with therapeutic doses of unfractionated heparin (UFH) or low-molecular-weight heparin (LMWH), followed by LMWH as the preferred agent for long-term monotherapy.

Novel oral anticoagulants have emerged that can rapidly change the therapeutic scenario in patients with/without cancer. These oral anticoagulants that achieve rapid inhibition of activated factor X or thrombin may offer an easier solution than LMWH but studies focusing on treatment of cancer-associated thrombosis with these agents are lacking. To date, some of these new agents have shown comparable efficacy and safety compared with traditional anticoagulants in randomized trials that included primarily patients without cancer.

One problem with this treatment is that there is no possibility to determine for how long the treatment for the VTE should be given.

D) Identification of cancer patients at risk of developing recurrent thrombotic events, diseases or disorder, in particular of VTE

Cancer patients are at high risk for recurrent thrombotic events, diseases or disorder, in particular of VTE. In a prospective cohort study, 20.7% of cancer patients developed recurrent VTE compared with 6.8% of patients without cancer. Cancer patients experience recurrence even within the first six month of anticoagulation. However, this risk varies depending on several parameters such as cancer site, cancer histology, or cancer stage.

There are few scores to predict VTE recurrence and only one is applicable for cancer patients. However, none of these scores for VTE recurrence prediction has been properly evaluated and none of them is used worldwide in clinical practice

NEED FOR A NEW RISK PREDICTION SCORE IN CANCER PATIENTS FOR THROMBOTIC EVENTS, DISORDERS OR DISEASES, AND A NEW RECURRENCE RISK PREDICTION SCORE FOR THROMBOTIC EVENTS, DISORDERS OR DISEASES IN CANCER PATIENTS.

Despite all the research done in the last years, the predictive capacity to identify cancer patients at risk of developing a first or recurrent thrombotic event, disorder or disease, in particular VTE, using the nowadays reference scores is very low. The performance of the Khorana score as described above still under study is as follows: The risk model was tested in a validation cohort of 1365 patients of whom 28 (2.1%) developed VTE. At the cut-off point for high risk (score 3), the model had a negative predictive value (probability of no VTE in those designated low risk) of 98.5%, a very low positive predictive value (probability of VTE in those designated high risk) of 7.1%, a low sensitivity (probability of high risk in those experiencing VTE) of 40.0%, and a specificity (probability of low risk in those not experiencing VTE) of 88% in the derivation cohort. Similarly, in the validation cohort, the model had a negative predictive value of 98.5%, a very low positive predictive value of 6.7%, a low sensitivity of 35.7%, and a specificity of 89.6%. Moreover, in the last years several studies have shown that the application of Khorana is not enough as the unique tool to identify cancer patients who should receive thromboprophylaxis^19-21. Scores to predict VTE recurrence have not been properly analysed regarding sensitivity, specificity and predictive values. From the data published so far, it can be deducted that the sensitivity thereof is 24.9% which would be extremely low.

Accordingly, there is a need for novel markers, including new genetic markers and clinic variables and specific combinations thereof that would successfully and advantageously predict which cancer patients are at high risk of developing a thromboembolic disease and/or thromboembolic disease complications such as - but not limited to - deep vein thrombosis and/or pulmonary embolism, whereby such a prediction would make it possible that preventive measures could be implemented as soon as possible to keep that risk at the lowest possible level.

There is also a need for novel markers, including new genetic markers and clinic variables and specific combinations thereof that would successfully and advantageously assist the diagnosis of a thromboembolic disease and/or thromboembolic disease complications such as - but not limited to - deep vein thrombosis and/or pulmonary embolism, whereby such a prediction would make it possible that preventive measures could be implemented as soon as possible to keep that risk at the lowest possible level.

There is also a need for novel markers, including new genetic markers and clinic variables and specific combinations thereof that would successfully and advantageously predict which cancer patients are at high risk of developing a recurrence of thromboembolic disease and/or thromboem bolic disease complications such as - but not limited to - deep vein thrombosis and/or pulmonary embolism, whereby such a prediction would make it possible that preventive measures could be implemented as soon as possible to keep that risk at the lowest possible level.

SUMMARY OF THE INVENTION

In a first aspect, the invention provides a method which is suitable to overcome the limitations of the methods used nowadays to estimate the thromboembolism risk and/or to diagnose the thromboembolic events for a subject suffering from cancer. In the following, preferred aspects are described:

1. A method for the thromboembolic event risk assessment in a subject suffering from cancer comprising the steps of determining in a sample isolated from said subject the presence of at least one allele of rs2232698, rs5985, rs6025 and rs4524, namely Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), , factor XIII Val34Leu

(rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524), whereby said presence is indicative of the risk of suffering a thromboembolic event (vein thrombosis, deep vein thrombosis and/or pulmonary embolism) and/or a recurrent thromboembolic event.

2. A method for the diagnosis of developing or suffering a thromboembolic disease or event or a recurrent thromboembolic event in a subject suffering from cancer comprising the steps of determining a sample isolated from said subject the presence of at least one allele of rs2232698, rs5985, rs6025 and rs4524, namel" Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), factor XIII Val34Leu (rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524) whereby said presence is indicative of the risk of suffering a thromboembolic event (vein thrombosis, deep vein thrombosis and/or pulmonary embolism) which is better than the risk assessment done by the methods nowadays in use, which is indicative of a risk of having a thromboembolic event and/or a recurrent thromboembolic event. The method as defined in any of the items 1 to 2 wherein the thromboembolic disease is selected from the group of fatal or non-fatal myocardial infarction, stroke, transient, ischemic attacks, peripheral arterial disease, vein thrombosis, deep vein thrombosis, pulmonary embolism or a combination thereof, preferably from venous thromboembolism, deep vein thrombosis and pulmonary embolism. A method for identifying a subject suffering from cancer in need of anticoagulant and/or antithrombotic therapy or in need of prophylactic antithrombotic and/or anticoagulant therapy comprising the steps of determining in a sample isolated from said subject the presence in at least one allele of polymorphisms rs2232698, rs5985, rs6025 and rs4524, namely Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), factor XIII Val34Leu (rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524), whereby said presence is indicative of having a decreased response to an antithrombotic and/or anticoagulant therapy or of being in need of early and aggressive antithrombotic and/or anticoagulant therapy or in need of prophylactic antithrombotic and/or anticoagulant treatment. The method as defined in any of items 1 to 4 further comprising determining one or more risk factor selected from the group consisting of body mass index (BMI), primary site of the tumor, tumor stage, family history of VTE, or additionally personal history of VTE, previous surgery, use of a central or peripheral catheter, chemotherapy, D-dimer, soluble p-selectin or additionally age, race, sex, smoking status, systolic blood pressure, diastolic blood pressure, hospitalization, plaster case, immobilization, surgery, trauma, hormonal contraceptive or hormone therapy, pregnancy, prolonged travel (>2 hours), collagen vascular diseases, heart failure, further medications, nephrotic syndrome, diabetes mellitus, low density

lipoprotein (LDL)-cholesterol level, high density lipoprotein (HDL)-cholesterol level, cholesterol level, triglyceride levels, pregnancy, or Khorana score. The method according to any of the items 1 to 5 wherein the assistance in the diagnosis of a VTE or prediction of a first VTE or of a recurrent VTE or of the need to receive thromboprophyasis or the need to prolong the thromboprophylasis is made in a subject during the procedure to identify whether the patient is suffering from cancer and/or during the procedure to characterize the TNM stage of the cancer. The method according to any of the items 1 to 5 wherein the assistance in the diagnosis of a VTE or prediction of a first VTE or of a recurrent VTE or of the need to receive thromboprophyaxis or the need to prolong the thromboprophylaxis is made in a subject at any time from the diagnosis of the cancer. The method according to any of the items 1 to 7 wherein the assistance in the diagnosis of a VTE or prediction of a first VTE or of a recurrent VTE or of the need to receive thromboprophyaxis or the need to prolong the thromboprophylaxis is made in a subject suffering from cancer and treated in an out-patient setting. The method according to any of claims 1 to 8, wherein the sample is an oral tissue sample, scraping or wash or a biological fluid sample, preferably saliva, urine or blood, or buccal cells. The method according to any one or more of items 1 to 9, wherein the presence or absence of the genetic variant is identified by amplifying or failing to amplify an amplification product from the sample, wherein the amplification product is preferably digested with a restriction enzyme before analysis and/or wherein the genetic variant is identified by hybridizing the nucleic acid sample with a primer label which is a detectable moiety. A method of determining the probability of an individual suffering from cancer of presenting a thromboembolism disease or event or a recurrent thromboembolism disease or event based on the presence of 1 to P classical risk factors and 1 to J polymorphisms selected from the group of rs2232698, rs5985, rs6025 and rs4524, namely Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), factor XIII Val34Leu (rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524), using the formula:

Probability (Y=llXi, X_n) = 1/ 1 + exp (β₀ + βι Xi + ... + β_η X_n + _f._{g Xf}-X_g +....β χ_ή·_Χί), wherein:

Probability (Y = 1 1 xi. Xn) = probability of presenting a thrombosis in a particular Cancer patient - with concrete and measurable characteristics in a number of variables 1, n,

- Exp = exponential natural base;

- β₀ = coefficient that defines the risk (the probability) of thrombosis non related with the variables 1 to n,

- βι = regression coefficient that expresses the risk (higher or lower) to present thrombosis associated with the value/presence of the predictor variable XI,

- xi = value taken by the predictor variable xl in an individual,

M β_η = regression coefficient that expresses the risk (higher or lower) to present thrombosis associated with the value/presence of the predictor variable X_n,

- X_n = value taken by the predictor variable X_n in an individual,

and

Pf.g = regression coefficient that expresses the risk (higher or lower) to present thrombosis associated with the combined presence of the predictor variables Xf and ^xg>

X_f = value taken by the predictor variable x, in an individual,

- X_g = value taken by the predictor variable X_f in an individual, - h i = regression coefficient that expresses the risk (higher or lower) to present thrombosis associated with the combined presence of the predictor variables X and Xi,

- X = value taken by the predictor varible X in an individual,

- Xi = value taken by the predictor variable x, in an individual.

12. A computer program or a cmputer-readable media containing means for carrying out a method as defined in any of items 1 to 11.

13. A kit comprising reagents for detecting the identity of the nucleotide selected from the group of rs2232698, rs5985, rs6025 and rs4524, namely Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), factor XIII Val34Leu (rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524).

14. A kit comprising reagents, e.g. primer pairs, for detecting the identity of the nucleotide of risk within a nucleic acid sequence selected from the group of SEQ. ID NO: 11 and 12; 15 and 16; 21 and 22; and 23 and 24.

15. The method or kit according to any of the items 1 to 14, wherein the predictive variables included are BMI, primary site of the tumor, tumor stage, family history of VTE, preferably included in function 1.

16. The method or kit of any one of items 1 to 15, wherein the sample is from a patient suffering from cancer.

The method provided according to the present invention overcomes the above limitations of known methods. It comprises the essential step of determining in a sample isolated from said subject the presence at least one of following genetic variants: rs6025, rs4524, rs2232698, and rs5985, which are indicative for the risk of suffering a thromboembolic event (in particular vein thrombosis, deep vein thrombosis and/or pulmonary embolism). This combination has been shown to have a surprinsingly increased capability for diagnostic purposes and risk assessment done by the methods nowadays in use.

In a further preferred embodiment, the two following SNPs are additionally determined: factor V Cambridge Arg306Thr (118203906), factor V Hong Kong Arg306Gly (rsll8203905).

In an even more preferred em bodiment, the above genetic variants are further combined with additional predictive variables, which are in particular selected from one or more of the following:

Body mass index (BMI) >25 is a risk factor,

Primary site of tumor (very high risk: stomach, glioma, and pancreas; high risk: lung, lymphoma, gynecologic, bladder, testicular; low risk: breast, colorectal, head and neck),

- Tumor stage (according to TNM staging system), higher tumor stages mea n a higher risk (as described in e.g. https://www.cancer.gov/about-cancer/diagnosis- staging/staging, which is the tumor staging system most widely used and acce^r,+orl; "J" refers to the size and extent of the main tumor, also called the primary ti :; "N" refers to the number of nearby lymph nodes that have cancer, "M" refers to whether the cancer has metastasized, which means that the cancer has spread from the primary tumor to other parts of the body),

Family history of VTE.

The TNM tumor staging can be further categorized as follows:

Primary tumor (T)

- TX - main tumor cannot be measured

- TO - main tumor cannot be found

- Tl, T2, T3, T4 - refers to the size and/or extent of the main tumor. The higher the number after the T, the larger the tumor or the more is has grown into nearby tissues.

Regional lymph nodes (N)

NX - Cancer in nearby Nymph nodes cannot be measured

NO - there is no cancer in nearby lymph nodes

Nl, N2, N3: refers to the number and location of lymph nodes that contain cancer. The higher the number after the N, the more lymph nodes that contain cancer.

Distant metastasis (M)

MX - metastasis cannot be measured

MO - Cancer has not spread to other parts of the body

Ml - cancer has spread to other parts of the body.

In a further preferred embodiment, the further variables as mentioned in Table 6b below are also determined.

In another aspect, the invention relates to methods for establishing the probability of patient suffering from cancer of presenting a thromboembolic event based on the presence of one or more of the polymorphisms mentioned above, optionally in combination with one or more predictive variables, e.g. as described above.

In another aspect, the invention relates to methods for establishing the probability of a patient suffering from cancer of presenting a recurrent thromboembolic event based on the presence of one or more of the polymorphisms mentioned above, optionally in combination with one or more predictive variables, e.g. as described above.

In another aspect, the invention relates to methods for the assistance in the diagnosis in a patient suffering from cancer, of a thromboembolic event, based on the presence of one or more of the genetic variants mentioned above, optionally in combination with one or more predictive variables, e.g. as described above, optionally, to confirm an earlier tentative diagnosis of a thromboembolic event.

In another aspect, the invention relates to methods for determining the need for preventive measurements in a patient suffering from cancer to prevent the development of a thromboembolic event and/or a recurrent thromboembolic event based on the prese~ of one or more of the polymorphisms mentioned above, optionally in combination with one or more predictive variables, e.g. as described above.

In another aspect, the invention relates to methods for the determination of a need for the prolonged treatment with anticoagulants in a patient suffering from cancer to prevent the development of a recurrent thromboembolic event based on the presence of one or more of the polymorphisms mentioned above, optionally in combination with one or more predictive variables, e.g. as described above.

"Thromboembolic event" in the context of this application should be understood as the alteration of the hemostasis that leads to the development of a blood clot (thrombo) inside a vascular vessel (artery or vein). The thromboembolic event can also obstruct the vascular vessel completely and/or become detached and obstruct another vascular vessel.

"Thromboembolic event" is meant to include in the present application among others the following conditions: arterial thrombosis, fatal- and non-fatal myocardial infarction, stroke, transient ischemic attacks, cerebral venous thrombosis, peripheral arteriopathy, deep vein thrombosis, vein thrombosis and pulmonary embolism.

"Recurrent thromboem bolic event" in the context of this application should be understood as a thromboembolic event in a subject who has already developed one or more

thromboembolic events.

"Thromboembolic event" in the context of this application is used interchangeably with "thromboembolism".

"Thromboembolic event" in the context of this application is used interchangeably with "thrombosis".

"Thromboembolic event" in the context of this application is used interchangeably with "thromboembolic complication".

"Thrombophilia" in the context of this application should be understood as encompassing disorders of hemostasis that predispose to thrombosis. Included are heritable deficiencies of the natural anticoagulants antithrombin, protein C, and protein S and un-common and common genetic variants in the genes encoding clotting factors and acquired

thrombophilias, such as antiphospholipid antibodies. All these disorders and diseases are well known to the person of skill in the art.

The terms "disease" and "disorder" shall be interpreted in the context of this application interchangeably,

"Mutation" or "genetic variant" in the context of this application should be understood as the change of the sequence and/or structure of a gene, resulting in a variant form which may be transmitted to subsequent generations, caused by the alteration of single base units in the DNA, or the deletion, insertion, or rearrangement of larger sections of genes or chromosomes. The terms "polymorphism" and "single nucleotide polymorphism" (SNP) are used herein interchangeably and relate to a genetic variant occurring when a single nucleotide in the genome or another shared sequence differs between members of species or between paired chromosomes in an individual. A SNP can also be designated as a mutation with low allele frequency greater than about 1% in a defined population. Single nucleotide polymorphisms according to the present application may fall within coding sequences of genes, non-coding regions of genes or the intronic regions between genes. For any given SNP, as mentioned herein, also all SNPs in high linkage disequilibrium are encompassed. Preferably, SNPs in high linkage disequilibrium are those with more than 70%, more preferred more than 80 %, even more preferred more than 95 %, linkage disequilibrium.

"Linkage disequilibrium" is well known to the person skilled in the art who will understand how to determine further SNPs in linkage disequilibrium to a given SNP.

It can be defined mathematically as follows:

A strong linkage disequilibrium is one with an r² value of more than 0.7, wherein r² is defined as follows:

(Pab - PaPitf

Pa( l " J¾)i¾»U ~ Pb)

where p_af, is the frequency of baplotypes having aide a at locus 1 and allele b at locus 2

The respective information can also be acquired in a straight-forward manner from public genome browsers like http://www.ensembl.org.

From such web resources, the skilled person can easily retrieve variants that are in linkage disequilibrium with a certain SNP.

The term "sample", as used herein, refers to any sample from a biological source and includes, without limitation, cell cultures or extracts thereof, biopsied material obtained from a mammal or extracts thereof, and blood, saliva, urine, feces, semen, tears, or other body fluids or extracts thereof. A preferred sample in the present context is blood or saliva, even more preferred buccal cells.

"Predictive variables" in the context of this application should be understood as those described in Table 1 above.

"Sociodemographic and clinical characteristics" in the context of this application should be understood as age, gender, diabetes mellitus, smoking, family history of thromboembolic event, personal history of thromboembolic event, pregnancy, and body mass index.

In a further aspect, the invention relates to a computer program or a computer-readable media containing means for carrying out any of the methods of the invention, in particular means which allow for the determination of the above preferred selection of genetic variants, and/or means for the determination of the above preferred additional variables.

In yet a further aspect, the invention relates to a kit comprising reagents for detecting genetic variants rs2232698, rs5985, rs6025, and rs4524 (i.e. Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), factor XIII Val34Leu (rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524)).

In a further preferred embodiment, the kit comprises those reagents which are suitable for detecting the preferred or more preferred combination of genetic variants, as listed above.

In an even further preferred embodiment, the kit additionally comprises reagents which are suitable for the determination of the additional variables, in particular, the combination of additional variables, as also mentioned above.

The person of skill in art, when informed about the preferred selection of SNPs and e.g. further variables, is well aware of methods and means on how to determine these variables. E.g. it is within the usual general knowledge of the person skilled in the art to determine probes or primers suitable to detect the above genetic variables. Also, it is well within the ambit of an average person of skill in the art to determine the additional variables, like BMI.

DETAILED DESCRIPTION OF THE INVENTION

The authors of the present invention have solved the problems identified above in the methods in use nowadays for the calculation of the risk in a subject to develop a thromboembolic event a nd/or recurrent thromboembolic event, as those terms have been defined above.

The authors of the present invention have identified a series of genetic variants which are associated with a particularly high risk of presenting a thromboembolic event and/or a recurrent thromboembolic event. These genetic variants show improved predictive and diagnostic value.

The present application solves the above-described limitations of the methods used nowadays to calculate a thromboembolic event risk and/or a recurrent thromboem bolic event risk and/or to diagnose a thromboembolic event, in particular of VTE, and in particular in cancer patients. This is achieved, if a particular combination (as described above) of genetic markers is used, which has been selected and evaluated by the inventors after a complex and genuine analysis of thousands of possible markers. Of the different possibilities to construct a genetic risk score (GRS), the inventors have determined a particular preferred combination and could show, as proven in the examples below, that it provided the best possible results. To calculate the genetic risk punctuation, the accumulated number of risk alleles from those SNPs listed in table 3 below that are present in each individual is considered. For each of the variants studied, every individual can have 0, 1 or 2 alleles of risk. On having calculated the summary of weighted risk alleles accumulated in the different set of the selected variants (n=8), for each individual a score that could go from 0 to 22 was given. A higher score means a higher risk. To establish the score, it is in an exemplary embodiment possible to use the coefficient for each genetic variable. You can have 0, 1 or 2 times (depending on the number of alleles found in a given sample, per SNP) that coefficient per each variant and the sum will give the genetic score. Using table 4 (and 0 or 1, respectively, per each of the further predictive variables, wi⁺^ "0" indicating the absence of this predictive variable, and "1" indicating its presence. However, for the determination of "stage", for TNM I and II the value of 0 is given, for TNM II and III a value of 1 is given, and for TNM IV a value of 2 is given; thereby one arrives at the sum for the further predictive variables. Both taken together, and preferably using the function 1 will result in the clinic-genetic overall score. The inventors have additionally generated new algorithms for the thromboembolic risk estimation which further assist the determination of a risk and the actual diagnosis, which in turn will lead to an indication to the person of skill in the art of whether or not treatment or preventive measures should be ta ken to prevent and/or treat a thromboembolic event, in particular VTE.

Table 3.

(Note: In table 3, NP means "not pertinent")

When prediction models are used, as for instance, for making treatment decisions, predictive risks may be categorized by using risk cut-off threshholds.

Those skilled in the art will readily recognize that the analysis of the nucleotides present according to the method of the invention in an individual's nucleic acid can be done by any method or technique capable of determining nucleotides present in a polymorphic site. As it is obvious in the art, the nucleotides present in the polymorphic markers can be determined from either nucleic acid strand or from both strands.

Once a biological sample from a subject has been obtained (e.g., a bodily fluid, such as urine, saliva, plasma, serum, or a tissue sample, such as a buccal tissue sample or a buccal cell, preferably a buccal cell), most preferably blood (plasma or serum), saliva or buccal cells, the detection of a sequence variation or allelic variant SNP is typically undertaken. Virtually any method known to the skilled artisan can be employed. One of the most direct and well known methods is to actually determine the sequence of either genomic DNA or cDNA and compare these sequences to the known alleles SNPs of the gene. This can be a fairly expensive and time consuming process. Nevertheless, this technology is quite common and is well-known to the average person of skill in the art.

Any of a variety of methods that exist for detecting sequence variations may be used in the methods of the invention. The particular method used is not important in the estimation of cardiovascular risk or treatment selection. Other examples of possible commercially available methods exist for high throughput SNP identification not using direct sequencing technologies, for example, lllumina's Veracode Technology, Taqman^® SNP Genotyping Chemistry and KASPar SNP genotyping Chemistry.

A variation on the direct sequence determination method is the Gene Chimp™ method available from Affymetrix^®. Alternatively, robust and less expensive ways of detecting DNA sequence variation are also commercially available. For example, Perkin Elmer adapted its TAQjnan Assay™ to detect sequence variation. Orchid Biosciences has a method called SNP- IT™ (SNP-ldentification technology) that uses primer extension with labeled nucleotide analogs to determine which nucleotide occurs at the position immediately 3' of an oligonucleotide probe, the extended base is then identified using direct fluorescence, an indirect colorimetric assay, mass spectrometry, or fluorescence polarization. Sequenom^® uses a hybridization capture technology plus MALDI-TOF (Matrix Assisted Laser Desorption/ionization-Time-of Flight mass spectrometry) to detect SNP genotypes with their MassARRAY™ system. Promega^® provides the READIT™ SNP/Genotyping System (U.S. Pat. No 6,159,693). In this method, DNA or RNA probes are hybridized to target nucleic acid sequences. Probes that are complementary to the target sequence at each base are depolymerized with a proprietary mixture of enzymes, while probes which differ from the target at the interrogation position remain intact. The method uses pyrophosphorylation chemistry in combination with luciferase detection to provide a highly sensitive and adaptable SNP scoring system. Third Wave Technologies^® has the Invader OS™ method that uses proprietary Cleavage enzymes, which recognize and cut only the specific structure formed during the Invader process. Invader OS^® relies on linear amplification of the signal generated by the Invader process, rather than on the exponential amplification of the target. The Invader OS assay does not utilize PCR in any part of the assay. In addition, there are a number of forensic DNA testing labs and many research labs that use gene-specific PCR, followed by restriction endonuclease digestion and gel electrophoresis (or other size separation technology) to detect restriction fragment length polymorphisms (RFLPs).

In various embodiments of any of the above aspects, the presence or absence of the SNPs is identified by amplifying or failing to amplify an amplification product from the sample, Polynucleotide amplifications are typically template-dependent. Such amplifications generally rely on the existence of a template strand to make additional copies of the template. Primers are short nucleic acids that are capable of priming the synthesis of a nascent nucleic acid in a template-dependent process, which hybridize to the template strand. Typically, primers are from ten to thirty base pairs in length, but longer sequences can be employed. Primers may be provided in double-stranded and/or single-stranded form, although the single-stranded form generally is preferred. Often, pairs of primers are designed to selectively hybridize to distinct regions of a template nucleic acid and are contacted with the template DNA under conditions that permit selective hybridization. Depending upon the desired application, high stringency hybridization conditions may be selected that will only allow hybridization to sequences that are completely complementary to the primers. In other embodiments, hybridization may occur under reduced stringency to allow for amplification of nucleic acids containing one or more mismatches with the primer sequences. Once hybridized, the template-primer complex is contacted with one or more enzymes that facilitate template-dependent nucleic acid synthesis. Multiple rounds of amplification, also referred to as "cycles," are conducted until a sufficient amount of amplification product is produced. Polymerase Chain Reaction

A number of template dependent processes are available to amplify the oligonucleotide sequences present in a given template sample. One of the best known amplification methods is the polymerase chain reaction. In PCR, pairs of primers that selectively hybridize to nucleic acids are used under conditions that permit selective hybridization. The term "primer", as used herein, encompasses any nucleic acid that is capable of priming the synthesis of a nascent nucleic acid in a template-dependent process. Primers may be provided in double- stranded or single-stranded form, although the single-stranded form is preferred. Primers are used in any one of a number of template dependent processes to amplify the target gene sequences present in a given template sample. One of the best known amplification methods is PCR, which is described in detail in U.S. Pat. Nos. 4,683,195, 4,683,202 and 4,800,156, each incorporated herein by reference. In PCR, two primer sequences are prepared which are complementary to regions on opposite complementary strands of the target gene(s) sequence. The primers will hybridize to form a nucleic acid primer complete if the target- gene(s) sequence is present in a sample. An excess of deoxribonucleoside triphosphates is added to a reaction mixture along with a DNA polymerase, e.g. Taq polymerase that facilitates template-dependent nucleic acid synthesis. If the target-gene(s) sequence primer complex has been formed, the polymerase will cause the primers to be extended along the target-gene(s) sequence by adding on nucleotides. By raising and lowering the temperature of the reaction mixture, the extended primers will dissociate from the target-gene(s) to form reaction products, excess primers will bind to the target-gene(s) and to the reaction products and the process is repeated. These multiple rounds of amplification, referred to as "cycles" are conducted until a sufficient amount of amplification product is produced.

The amplification product may be digested with a restriction enzyme before analysis. In still other embodiments of any of the above aspects, the presence or absence of the SNP is identified by hybridizing the nucleic acid sample with primer labeled with a detectable moiety. In other embodiments of any of the above aspects the detectable moiety is detected in an enzymatic assay, radio assay, immunoassay or by detecting fluorescence. In other embodiments of any of the above aspects, the primer is labeled with a detecta ble dye (e.g., SYBR Green 1, YO-PRO-1, thiazole orange, Hex, pico green, edans, fluorescein, FAM, or TET). In other embodiments of any of the above-aspects, the primers are located on a chip. In other embodiments of any of the above aspects, the primers for amplification are specific for said SNPs.

Another method for amplification is the ligase chain reaction ("LCR"). LCR differs from PCR because it amplifies the probe molecule rather than producing an amplicon through polymerization of nucleotides. In LCR, two complementary probe pairs are prepared a nd in the presence of a target sequence, each pair will bind to opposite complementary strands of the target such that they abut. In the presence of a ligase, the two probe pairs willing to form a single unit. By temperature cycling, as in PCR, bound ligated units dissociate from the target and then serve as "target sequences" for ligation of excess probe pairs. U.S. Pat. No. 4,883,750, incorporated herein by reference, describes a method similar to LCR for binding probe pairs to a target sequence. Isothermal Amplification

As isothermal amplification method, in which restriction endonucleases and ligases are used to achieve the amplification of target molecules that contain nucleotide 5'-[[alpha]-thio}- triphosphates in one strand of a restriction site also may be useful in the amplification of nucleic acids in the present invention. In one embodiment, loop-mediated isothermal amplification (LAMP) method is used for single nucleotide polymorphism (SNP) typing.

Strand Displacement Amplification

Strand Displacement Amplification (SDA) is another method of carrying out isothermal amplification of nucleic acids which involves multiple rounds of strand displacement and synthesis, i.e., nick translation. A similar method, called Repair Chain Reaction (RCR), involves annealing several probes throughout a region targeted for amplification, followed by a repair reaction in which only two of the four bases are present. The other two bases can be added as biotinylated derivatives for easy detection.

Transcription-Based Amplification

Other nucleic acid amplification procedures include transcription-based amplification systems, including nucleic acid sequence based amplification. In nucleic acid sequence based amplification, the nucleic acids are prepared for amplification by standard phenol/chloroform extraction, heat denaturation of a clinical sample, treatment with lysis buffer and mini-spin columns for isolation of DNA and RNA or guanidinium chloride extraction of RNA. These amplification techniques involve annealing a primer, which has target specific sequences. Following polymerization, DNA/RNA hybrids are digested with RNase H while double stranded DNA molecules are heat denatured again. In either case the single stranded DNA is made fully double stranded by addition of second target specific primer, followed by polymerization. The double-stranded DNA molecules are then multiply transcribed by a polymerase such as T7 or SP6. In an isothermal cyclic reaction, the RNA's are revers transcribed into double stranded DNA, and transcribed once against with a polymerase such as T7 or SP6. The resulting products, whether truncated or complete, indicate target specific sequences.

Other amplification methods may be used in accordance with the present invention. In one embodiment, "modified" primers are used in a PCR-like template and enzyme dependent synthesis. The primers may be modified by labelling with a capture moiety (e.g., biotin) and/or a detector moiety (e.g., enzyme). In the presence of a target sequence, the probe binds and is cleaved catalytically. After cleavage, the target sequences released intact to be bound by excess probe. Cleavage of the labelled probe signals the presence of the target sequence. I n another approach, a nucleic acid amplification process involves cyclically synthesizing single-stranded RNA ("ssRNA"), SSDNA, and double-stranded DNA (dsDNA), which may be used in accordance with the present invention. The ssRNA is a first template for a first primer oligonucleotide, which is elongated by reverse transcriptase (RNA- dependent DNA polymerase). The RNA is then removed from the resulting DNA-RNA duplex by the action of ribonuclease H (RNase H, and RNase specific RNA in duplex with either DNA or RNA). The resultant ssDNA is a second template for a second primer, which also includes the sequences of an RNA polymerase promoter (exemplified by T7 RNA polymerase) 5' to its homology to the template. This primer is then extended by DNA polymerase (exemplified by the large "Klenow" fragment of E coli DNA polymerase I), resulting in a double-stranded ONA ("dsDNA") molecule, having a sequence identical to that of the original RNA between the primers and having additionally, at one end, a promoter sequence. This promoter sequence can be used by the appropriate RNA polymerase to make many RNA copies of the DNA. These copies can then re-enter the cycle leading to very swift amplification. With proper choice of enzymes, this amplification can be done isothermally without addition of enzymes at each cycle. Because of the cyclical nature of this process, the starting sequence can be chosen to be in the form of either DNA or RNA.

Method of Nucleic Acid Separation

It may be desirable to separate nucleic acid products from other materials, such as template and excess primer. In one embodiment, amplification products are separated by agarose, agarose acrylamide or polyacrylamide gel electrophoresis using standard methods (Sambrook et al., 1989, see infra). Separated amplification products may be cut out and eluted from the gel for further manipulation . Using low melting point agarose gels, the separated band may be removed by heating the gel, followed by extraction of the nucleic acid. Separation of nucleic acids may also be effected by chromatographic techniques known in the art. There are many kinds of chromatography which may be used in the practice of the present invention, including adsorption, partition, ion-exchange, hydroxylapatite, molecular sieve, reverse-phase, column, paper, thin-layer, and gas chromatography as well as H PLC. In certain embodiments, the amplification products are visualized. A typical visualization method involves staining of a gel with ethidium bromide and visualization of brands under UV light. Alternatively, if the amplification products are integrally labeled with radio- or fluorometrically-labeled nucleotides, the separated amplification products can be exposed to X-ray film or visualized with light exhibiting the appropriate excitatory spectra.

Alternatively, the presence of the polymorphic positions according to the methods of the invention can be determined by hybridization or lack of hybridization with a suitable nucleic acid probe specific for a polymorphic nucleic acid but not with the non-mutated nucleic acid.

By "hybridize" is meant a pair to form a double-stranded molecule between complementary polynucleotide sequences, or portions thereof, under various conditions of stringency. For example, stringent salt concentration will ordinarily be less than about 750 mM NaCI and 75 mM trisodium citrate, preferably less than about 500 mM NaCI and 50 mM trisodium citrate, and more preferably less than about 250 mM NaCI and 25 mM trisodium citrate. Low stringency hybridization can be obtained in the absence of organic solvent, e.g., formamide, while high stringency hybridization can be obtained in the presence of at least about 35% formamide, and more preferably at least a bout 50% formamide. Stringent temperature conditions will ordinarily include temperatures of at least about 30°C, more preferably of at least about 37°C, and most preferably of at least about 42°C. Varying additional parameters, such as hybridization time, the concentration of detergent, e.g., sodium dodecyl sulfate (SDS), and the inclusion or exclusion of carrier DNA, are all well known to those skilled in the art. Various levels of stringency are accomplished by combining these various conditions as needed. I n a preferred em bodiment, hybridization will occur at 30°C in 750 mM NaCI, 75 mM trisodium citrate, and 1% SDS. In a more preferred embodiment, hybridization will occur at 37°C in 500 mM NaCI, 50 mM trisodium citrate, 1% SDS, 35% formamide, and 100 μg/ml denatured salmon sperm DNA (ssDNA). In a most preferred embodiment, hybridization will occur at 42°C in 250 mM NaCI, 25 mM trisodium citrate, 1% SDS, 50% formamide, and 200 μg/ml ssDNA. Useful variations on these conditions will be readily apparent to those skilled in the art.

For most applications, washing steps that follow hybridization will also vary in stringency. Wash stringency conditions can be defined by salt concentration and by temperature. As above, wash stringency can be increased by decreasing salt concentration or by increasing temperature. For example, stringent salt concentration for the wash steps will preferably be less than about 30 mM NaCI and 3 mM trisodium citrate, and most preferably less than about 15 mM NaCI and 1.5 mM trisodium citrate. Stringent temperature conditions for the wash steps will ordinarily include a temperature of at least about 25°C, more preferably of at least about 42°C, and even more preferably of at least about 68°C. In a preferred embodiment, wash steps will occur at 25°C in 30 mM NaCI, 3 mM trisodium citrate, and 0.1% SDS. In a more preferred embodiment, wash steps will occur at 42°C in 15 mM NaCI, 1.5 mM trisodium citrate, and 0.1% SDS. In a more preferred embodiment, wash steps will occur at 68°C in 15 mM NaCI, 1.5 mM trisodium citrate, and 0.1% SDS. Additional variations on these conditions will be readily apparent to those skilled in the art. Hybridization techniques are well-known to those skilled in the art and are described, for example, in Benton and Davis (Science 196: 180, 1977); Grunstein and Hogness (Proc. Natl. Acad. Sci., USA 72:3961, 1975); Ausubel et al. (Current Protocols in Molecular Biology, Wiley Interscience, New York, 2001); Berger and Kimmel (Guide to Molecular Cloning Techniques, 1987, Academic Press, New York); and Sambrook et al., Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, New York, 1989.

Nucleic acid molecules useful for hybridization in the methods of the invention include any nucleic acid molecule which exhibits substantial identity so as to be able to specifically hybridize with the target nucleic acids. Polynucleotides having "substantial identity" to an endogenous sequence are typically capable of hybridizing with at least one strand of a double-stranded nucleic acid molecule. By "substantially identical" is meant a polypeptide or nucleic acid molecule exhibiting at least 50% identity to a reference amino acid sequence or nucleic molecule exhibiting at least 50% identity to a reference amino acid sequence or nucleic acid to the sequence used for comparison. Sequence identity is typically measured using sequence analysis software (for example, Sequence Analysis Software Package of the Genetics Computer Group, University of Wisconsin Biotechnology Center, 1710 University Avenue, Madison, Wis. 53705, BLAST, BESTFIT, GAP, or PILEUP/PRETTYBOX programs). Such software matches identical are similar sequences by assigning degrees of homology to various substitutions, deletions, and/or other modifications. Conservative substitutions typically include substitutions within the following groups: glycine, alanine, valine, isoleucine, leucine, aspartic acid, glutamic acid, asparagine, glutamine, serine, threonine, lysine, arginine, and phenylalanine, tyrosine. I n an exemplary approach to determining the degree of identity, a BLAST program may be used with a probability score between e<"3> and e<"100> indicating a closely related sequence.

A detection system may be used to measure the absence, presence and amount of hybridization for all of the distinct sequences simultaneously. Preferably, a scanner is used to determine the levels and patterns of fluorescence.

The specific sequences which can be used for the detection of the polymorphisms are described in table 3 above. Preferred SNPs are defined in the claims.

Method to establish the risk status.

Another object of the present invention is the development of an algorithm - in close connection and relationship to the SNPs (and optionally further variables) to be determined - to estimate the risk of a patient suffering from cancer to develop and/or to being suffering a thromboembolic event or a recurrent thromboembolic event. The algorithm is shown as function 1.

Function 1

Estimating the risk of thromboembolic event in a patient with cancer, either in the process of being diagnosed, just diagnosed or in whom chemotherapy is going to be initiated.

The individual estimation of the risk of thromboembolic event is based on a logistic regression model. The aim of this model is to calculate the probability that a person has of presenting thromboembolic event and/or a recurrent event according to his/her genetic, sociodemographic and clinical characteristics. To calculate this probability we use the following equation:

Proba bility (Y=UX_1; X_n) = 1/ 1 + exp (β₀ + βι Χι + ... + β„ X„ + Pf._g XfX_g +....Ρ_Η ¾· wherein:

Probability 1 I xi. Xn) = probability of presenting a thromboembolic event in a particular cancer patient with concrete a nd measureable characteristics in a number of variables 1, n. This probability could range between 0 and 1 (This is the probability considering all the variables included in the algorithm and it can be expressed as 0 - 1 or alternatively as a percentage from 0-100%. "0" means low probability and 1 (or 100%) means a high probability. The GRS score is one of the variables included and the GRS can range from 0 to 22,a s described above);

- Exp = exponential natural base;

- β₀ = coefficient that defines the risk (the probability) of thromboembolic event non-related with the variables 1 to n. This coefficient can take a value from -∞ to +∞ and is calculated as the natural logarithm of the incidence of thromboembolic event in the population:

- βι = regression coefficient that expresses the risk (higher or lower) to present thromboembolic event associated with the value/presence of the predictor variable Xi. This coefficient can take a value from -∞ to +∞.

- xi = value taken by the predictor variable xi in an individual. The range of possible values depends on the variable;

- β_η = regression coefficient that expresses the risk (higher or lower) to present a thromboembolic eventAssociated with the value/presence of the predictor variable X_n. This coefficient can take a value from -∞ to +∞;

- X_n = value taken by the predictor variable Xn in an individual. The range of possible values depends on the variable.

In addition, the model includes the effect of the combination of some variables in terms of interaction or modification of the effect. That is, the effect size (regression coefficient) of a single variable (x_f) can be Pf but if this variable is present in combination with another variable (X_g) the effect size may vary (increase or decrease). To consider the effect size of the variable X_f it is therefore necessary to consider not only the Pf but also a second regression coefficient Pf._g by adding the Pf and the Pf._g. Thus:

- Pf.g = regression coefficient that expresses the risk (higher or lower) to present

thromboembolic event associated with the combined presence of the predictor variables Xf and x_g. This coefficient can take a value from -∞ to +∞;

- X_f = value taken by the predictor variable x, in an individual. The range of possible values depends on the variable;

- X_g = value taken by the predictor variable X_f in an individual. The range of possible values depends on the variable;

- h i = regression coefficient that expresses the risk (higher or lower) to present a

thromboembolic event associated with the combined presence of the predictor variables Xf, and Xi This coefficient can take a value from -∞ to +∞;

- X_h = value taken by the predictor variable Xf, in an individual. The range of possible values depends on the variable;

- Xi = value taken by the predictor variable x, in an individual. The range of possible values depends on the variable;

The variables included in the model and the regression coefficients of each of these variables are shown in Table 4.

Table 4

"GRS" (genetic risk score) here refers to the GRS for the four preferred SNPs, as mentioned above, and Table 5 below.

"Family" refers to the family history of VTE.

"Stage " is the Stage of the TNM tumor staging system described above. This staging system is well accepted and can be used for the present tumor stage definition. "Lower" and "upper" are defined as the estimated lowest possible value and the estimated highest posible value according to the present data and regression coefficient

"KhHR" means High risk based on the Khorana score (i.e. +1), and "KhVHR" means very high risk based on the Khorana Score (i.e. +2).

The GRS (i.e. genetic risk score) can be formed by the genetic variants included in table 5.

Table 5

Surprisingly, the combination of genetic variants, in particular in the combination described above as preferred (those in table 5), and even more preferred in combination with clinical variables included in the present invention (e.g. as set forth in table 4) have proved to be capable to determining the risk of a patient with cancer to develop a thromboempolic disease or event or a recurrent thromboembolic disease or event with a higher accuracy than that obtained using the methods nowadays in use or published functions including genetic information. The additional use of the above described function further assists these methods. This is particularly applicable to patients which have not yet undergone chemotherapy.

Surprisingly, the preferred combination of genetic variants, in particular in combination with clinical variables included in the present invention and further preferably using the function described in function 1 have proved to be capable to assist in the diagnosis of a thromboembolic disease or event in a patient suffering from cancer with a higher accuracy that that obtained using the methods nowadays in use or published functions including genetic information.

By the use of the functions described, a personalized risk for a patient with cancer is obtained for the development of a thromboem bolic event or a recurrent thromboem bolic event, in particular fatal- and non-fatal-myocardium infarction, stroke, transient ischemia attack, peripheral ateriopathy, deep vein thrombosis, pulmonary embolism or a combination thereof.

By the use of the above GRS, optionally in combination with further clinical risk factors, and optionally using the above described function, a personalized risk for a patient with cancer is obtained for the development of a thromboembolic event or a recurrent thromboembolic event, in particular fatal- and non-fatal-myocardium infarction, stroke, transient ischemia attack, peripheral ateriopathy, deep vein thrombosis, pulmonary embolism or a combination thereof. Surprisingly, the VTE risk estimation can be performed at the same time the characterization of the cancer process is being performed by the pysician even before the consideration of a chemotherapy is established. This is very relevant as close to half of the VTE events in cancer patients are occuring even before chemotherapy is initiated.

Example 1

The aim of this study was to evaluate the capability of a new genetic risk score and a new clinical-genetic algorithm (the so called "TiC-Onco") for the identification of cancer patients in outpatient setting at risk of developing VTE in comparison to the standard risk assessment method.

Methods

Study design and participants

The study protocol was approved by the participant hospitals' institutional review boards. Signed, informed consent was obtained from each patient.

This study - the ONCOTHRO MB 12-01 study - is a multicentric observational cohort study involving an 18 month monitoring period with analysis at 6, 12 and 18 months. This example presents the results for the first 6 months. The initial study subjects were 406 out-patients, all over 18 years of age, with a recent diagnosis (following standard procedures) of colorectal, oesophago-gastric, lung, or pancreatic cancer. All had an ECOG/WHO/Zubrod score (One of several well known scores for the classification of the performance of Cancer patients: The Eastern Cooperative Oncology Group (ECOG) score, also called the WHO or Zubrod score (after C. Gordon Zubrod), runs from 0 to 5, with 0 denoting perfect health and 5 death:

• 0 - Asymptomatic (Fully active, able to carry on all predisease activities without

restriction)

• 1 - Symptomatic but completely ambulatory (Restricted in physically strenuous

activity but ambulatory and able to carry out work of a light or sedentary nature. For example, light housework, office work)

• 2 - Symptomatic, <50% in bed during the day (Ambulatory and capable of all self care but unable to carry out any work activities. Up and about more than 50% of waking hours)

• 3 - Symptomatic, >50% in bed, but not bedbound (Capable of only limited self-care, confined to bed or chair 50% or more of waking hours)

• 4 - Bedbound (Completely disabled. Cannot carry on any self-care. Totally confined to bed or chair)

• 5 - Death) of 0 - 2 and were candidates for systemic outpatient chemotherapy. All were treated according to standard guidelines.

The selection criteria were as follows: • over 18 years of age

• recent diagnosis of cancer of the following types: colorectal, oesophago-gastric, lung or pancreatic.

• ECO/WHO/Zubrod score of 0 - 2

• Candidates for systemis outpatient chemotherapy according to standard guidelines.

• No thromboprophylactic therapy deemed mandatory by the treating oncologist.

Out of the 406 patients, 391 of them fulfilled those criteria. These latter patients formed the study population and were monitored over the next 6 months for VTE events (with treatment provided as required). The Khorana score (reference tool) and the proposed inventive TiC- Onco score (index tool) were calculated retrospectively for each patient and their accuracy in terms of predicting the observed VTE events was compared.

Diagnosis of VTE events

Deep vein thrombosis in the lower limbs was diagnosed by ultrasound or ascending venography. Pulmonary embolism was diagnosed by ventilation-perfusion lung scanning, pulmonary angiography, or spiral computed tomography. Visceral vein thrombosis was diagnosed by ultrasound, spiral computed tomography or magnetic resonance imaging. Intracranial venous thrombosis was diagnosed by magnetic resonance imaging.

Development of the TiC-Onco risk score

The TiC-Onco risk score tool was developed in three steps:

1) Development of a genetic risk score.

391 patients were genotyed for the genes shown in Table 6b using blood extracted at the time of diagnosis, employing TaqMan genotyping assays and the EP1 Fluidigm platform (an efficient endpoint PCR system for high-sample- throughput SNP genotyping).

We hypothesized that primary VTE risk assessment can be improved by using genetic risk scores with more genetic markers than just the broadly used FVL- rs6025 and prothrombin gene PT-rsl799963. Very specific genetic variants which were hypothezised to be associated to VTE, out of the existing broad range of possibilities: rs6025, and rs4524 in the gene coding for factor V in the coagulation pathway, rsl799963 in the gene coding for factor II, rsl801020 in the gene coding for factor XII, rs5985 in the gene coding for factor XIII, rsl21909548 in the gene coding for SERPINC1, and rs2232698 in the gene coding for SERPINA10 plus the variants for the identification of the presence of Al blood group (rs8176719, rs7853989, rs8176743, rs8176750).

At 6 months, multivariate logistic regression analysis was performed to determine the weight of each genetic variable in the appearance of a VTE event. The final genetic risk score was determined using the genetic variants associated with an increased risk of VTE in the multivariate model (ρ≤0·25).

Table 6a shows the tested further predictive variables.

VTE No- VTE p valun

"Esof = Oesophagal

Table 6b: tested genetic variables

Table 6c

Tumor type Colon Pancreas Lung Esofagous Stomach Total

Total 163 72 S7 14 55 391

Patients (%) 41,69 18,41 22,25 3,58 14,07

Control 141 43 76 12 48 320

Case 22 29 11 2 7 71

Cases (%) 13,50 40,28 12,64 14,29 12,73 Table 6d

Stage

I+H ill IV

Colon 29 74 60

Pancreas 18 12 42

Lung 9 34 44

Esofagous 3 5 6

Stomach 12 14 29

Total 71 139 181

Table 6e

Table 6f

VTE, n (%) No-VTE, n (%)

Death 22 (30.99) 36 (11,25)

Esof or esofagus is meant to be "oesophagus".

2) Selection of predictive clinical variables associated with the development of VTE.

Data were collected from all patients on the clinical risk factors cited in the literature²² as being associated with VTE and that could be known at the time of diagnosis: primary tumour site, tumour node metastasis stage, body mass index (BMI), use of tobacco, age, sex, family (first degree) history of VTE, the presence of diabetes, hypertension, high blood cholesterol level, the Khorana score, previous surgery, number of platelets, number of leukocytes, and immobilization. The risk of VTE associated with the primary tumour site (low, high and very high) was categorized as when determining the Khorana score¹⁶. The risks associated with platelet and leukocyte numbers were categorized using the same cut-offs as for the Khorana score¹⁶.

At 6 months, univariate analysis was performed (Wilcoxon and χ² tests) to determine which of these variables were associated with the appearance of a VTE event. Those associated with an increased risk of VTE (ρ≤0·25) or with published evidence were selected.

3) Development of the clinical-genetic model.

The genetic risk score and the clinical variables selected were subjected to multivariate logistic regression analysis using an AlC-based backward selection process.

Comparing the Khorana and Tic-Onco risk score

The risk prediction capacity of the Khorana and TiC-Onco risk score was evaluated using the c-statistic, which represents the area under the receiver operating characteristic (ROC) curve (larger values indicate better discrimination)²³. Standard measures of sensitivity, specificity, positive and negative predictive value (PPV and NPV), diagnostic odds ratio (DOR), and positive and negative likelihood ratios (PLR and NLR)²⁴ were determined for specific cut-off points. The cut-off for high risk as determined using the Khorana score was set at >3 (the normal cut-off value), and for the TiC-Onco score either as the point on the ROC curve giving the same specificity as provided by the Khorana score, or the point providing the best Youden Index. In order to allow the Tic-Onco score to provide three risk categories - high, intermediate and low risk - the cut-offs used were the same specificity as provided by the Khorana score (distinguishing high from intermediate risk), and a sensitivity of close to 90% (distinguishing between intermediate and low risk).

Statistical analysis

All calculations were performed using R statistical software (version 3.1.3)²⁵ and MedCalc for Windows v.16.4.3 (MedCalc Software, Ostend, Belgium).

Number of patients needed to treat

To assess the effect of the TiC-Onco risk score in terms of preventing VTE events, the number of patients needed to treat (NNT) was determined for both scores²⁶. It was assumed that prophylactic medication would reduce cancer-associated VTE by 46%²⁷.

Results

Patient characteristics

Table 6 shows the clinical and demographic characteristics of the 391 patients at the start of the study. For each variable, the number and percentage of patients who experienced a VTE, or not, at some point in the 6 month study period, are shown. The overall incidence of VTE was 18.16%. Patients suffering from pancreatic cancer experienced VTE at a significantly higher frequency (40.28%) than patients with other type of cancers (p<0.001) (Table 6).

Development of the Tic-Onco risk model

Table 7 shows the genetic and clinical markers that were significantly associated by multivariate analysis with a VTE event, and thus selected for inclusion in the TiC-Onco risk score model.

Table 7a rs p value

Table 7b

Variable p value

Accuracy and validation of the risk model

The TiC-Onco score showed an area under the ROC curve of 0.734 (0.673-0.794), a sensitivity of 49.30%, and a specificity of 81.25%. Its PPV was 36.84%, NPV 87.84%, PLR 2.63, NLR 0.62, and DOR 4.21 (Table 8). The Khorana score showed a significantly lower capacity to distinguish between patients who experienced/did not experience a VTE event (0.734 vs. 0.580; ρ<0·001). The sensitivity of the TiC-Onco score was significantly higher than that of the Khorana (49.30% vs. 22.54%; ρ<0·002), while the specificities of both scores were similar (81.25% vs. 81.76%; p<0.949). The PPV of the TiC-Onco score was significantly higher than that of the Khorana score (36.84% vs. 21.62%; p=0.049), while their NPV scores were similar (87.84% vs. 82.54%; p=0.085). The NLR and DOR of the TiC-Onco score were also significantly better (Table 8).

Table 8

AUC AUC (95% Ci]

Sensitivity (%)

Specificity {%)

PPV {%)

NPV { )

LK+ (95%Ci]

lit- (95¾C1)

DOR

(TiC-Onco 1 and 2 refer to two differnt points in the same AUC curve. The cutt-off point for TiC-Onco 1 is selected by a mathematical model selecting the best combination of sensitivity and specificity (the point providing the best Youden Index . The cut-off for TiC-Onco 2 is selected to have a specificity similar to that of Khorana.)

Tables 9 and 10 show the distribution of patients deemed likely/not likely to experience a VTE event according to the Khorana score, and for the TiC-Onco score (with the cut-off set at the same specificity as the former score). The great majority of patients who suffered a VTE event (77.46%) were identified by the Khorana score as being at low or moderate risk (values 0, 1 and 2). Among these 55 patients, however, 17 (31%) were detected as high risk patients by the TiC-Onco score. When the cut-off for high risk was taken as the best Youden Index, the TiC-Onco score returned significantly better predictions of risk than the Khorana score, especially in terms of sensitivity (85.92% vs. 22.54%, ρ<0·001) (Table 8). In this scenario, of the 55 patients who experienced a VTE event (but who were classified as not being at high risk by the Khorana score), 40 (73%) were detected as high risk patients by the TiC-Onco score.

Table 9 Khorana VTE No-VTE Patients (n) | Patients ¾ VTE Cases

Total 71 320 391

Table 10

Table 11 shows the NNT values for if all patients included in the study had been treated (NNT = 12.0), if only the patients with a Khorana score of >3 had been treated (NNT = 10.1), or if only patients with a high risk TiC-Onco score (with the cut-off set at the same specificity as the Khorana score) had been treated (NNT = 5.9).

Table 11

Treatment group NNT

All cancer patient 12,0

Khorana > 3 10,1

TiC-Onco > cut-off 5,9 "Cut-off" in that regard means that the collected points after carrying out the evaluation according to the selected score is at 3 or higher.

The Khorana-score is as follows:

Cancer Type: Stomach +2

Pancreas +2

Lung +1

Lymphoma +1

Gynecologic +1

Bladder +1

Testicular +1

Other 0

Pre-chemotherapy platelet count > 350 x 10⁹/l no: 0 yes: +1

Hemoglobin level < 10 g/dl or using RBC growth factors no: 0 yes: +1

Pre-chemotherapy leukocyte count > 11 x 10⁹/l no: 0 yes: +1

BMI > 35 kg/m² no: 0 yes: +1

Thus, if a patient would - in an example - have a history of stomach cancer (two "points"), and a BMI of more than 35 kg/m², this patient would have a score of "3" and would thus be at the cut-off point.

All analysis were performed using R statistical software (version 3.1.3)²⁵ and MedCalc for Windows, version 16.4.3 (MedCalc Software, Ostend, Belgium).

Positive Predictive Value (PPV) and Negative Predictive Value (NPV) are defined as is well- known to the person skilled in the art, as reflected e.g. in Wikipedia: The positive and negative predictive values (PPV and NPV respectively) are the proportions of positive and negative results in statistics and diagnostic tests that are true positive and true negative results, respectively, (Fletcher, Robert H. Fletcher ; Suzanne W. (2005). Clinical epidemiology : the essentials (4th ed.). Baltimore, Md.: Lippincott Williams & Wilkins. p. 45. ISBN 0-7817- 5215-9.) The PPV and NPV describe the performance of a diagnostic test or other statistical measure. A high result can be interpreted as indicating the accuracy of such a statistic. The PPV and NPV are not intrinsic to the test; they depend also on the prevalence.

"LR" (+ or -) are likelihood-ratios. They are to be understood as known to the person skilled in the art, i.e. the Likelihood Ratio (LR) is the likelihood that a given test result would be expected in a patient with the target disorder compared to the likelihood that that same result would be expected in a patient without the target disorder.

"CI" is the confidence interval, again well known to the person skilled in the art, i.e. a confidence interval (CI) is a type of interval estimate of a population parameter. It is an observed interval (i.e., it is calculated from the observations), in principle different from sample to sample, that potentially includes the unobservable true parameter of interest.

"DOR" is the diagnostic odds ratio, again well known to the person skilled in the art, i.e. In medical testing with binary classification, the diagnostic odds ratio is a measure of the effectiveness of a diagnostic test. It is defined as the ratio of the odds of the test being positive if the subject has a disease relative to the odds of the test being positive if the subject does not have the disease.

Discussion

When deciding whether to use primary antithrombotic prophylaxis in ambulatory cancer patients who are candidates for receiving Chemotherapy, a clinician needs to determine the patient^'s risk of VTE and weigh the magnitude of benefit with antithrombotic prophylaxis against the risk of bleeding. Despite the awareness of the Scientific Societies about cancer associated VTE, the predictive capability of existing tools is still sub-optimal. This could explain the limited use of thrombo-prophylaxis.

Here, we have presented the development a nd capabilities of a new predictive score showing significantly better predictive capabilities than those by the Khorana Assessment tool.

The incidence of VTE in the studied population at six months of follow up is 18.16% (71 VTE cases in 391 patients).

In this analysis of data from an ongoing observational study we have identified 4 clinical and 4 genetic variants that were independently predictive of VTE in outpatient cancer patients candidate for chemotherapy. In combination, these parameters achieved a much better predictive capability than known parameter combinations. With those 8 variants the patients can be categorized into two categories; high and low risk for VTE depending on whether the score is higher or lower than the cut-off defined to obtain the same specificity than Khorana. The rate of VTE over the period of follow up of 6 months is 36.84% in the high risk patients and 12.16% in the low risk patients. However, when the three-tier TiC-Onco risk category system was contemplated (explained in methods), 36.84% of the high risk, 18.30% of the moderate risk, and 5.59% of the low risk patients experienced a VTE event. In comparison the rates in the low, intermediate and high Khorana risk categories were 12.96%, 18.81%, and 21.62%, respectively.

VTE is a multifactorial, complex disease that results from a combination of genetic and acquired risk factors. The heritability of VTE has been estimated to be at about 60%. The genetic factors underlying the risk of VTE include some well-established genetic variants such as factor V Leiden and prothrombin variant G20210A and new variants coming out from GWAS studies. We could show with the present invention that a particular selection of some of the variants from GWAS studies can be integrated with the well-established to result in new GRSs, and in a very significant improvement in the prediction of VTE over the classical methods is observed in non-cancer patients.

The majority of genetic studies existing in the prior art have excluded individuals with cancer- related thrombosis and the relatively few studies that have been performed have been mainly focused on factor V Leiden and prothrombin G20210A genetic variants and have reported conflicting results. The conflicting results are most likely due because the analysis was done on single-marker marginal analysis. That standard approach may suffer from low power and poor reprod ucibility. One useful strategy to solve those problems is through marker-set analysis, where a set of genetic markers are assembled. That is the approach we have used in the present work.

For the genetic variant rs5985 (genetic variant in the gene coding for factor XIII in the coagulation pathway) conflicting results have been reported. Genetic variant rs2232698 (genetic variant in the gene coding for Serpin A10) has been rarely studied.

The resulting GRS using our approach was the variable in multivariate analysis associated with VTE with the highest p value (in TiC-Onco). This is in line with the known heritability of VTE (60%).

As cancer associated VTE is a multifactorial entity where clinical and genetic factors are acting, we use a multivariate approach of feature selection allowing us to identify a subset or a combination of informative genetic variants and non-genetic variables that underlies the risk of developing VTE. That approach is capable of capturing the multifactorial characteristics of VTE.

Taking into account that the distribution of patients through the different Khorana scores is similar to that previously communicated for the same follow up we have demonstrated that the predictive capability of TiC-Onco is significantly better tha n those showed by the Khorana Score. This superiority is demonstrated by a better a rea under the ROC curve, better sensitivities and higher likelihood positive and negative ratios and higher negative predictive value. However, in the comparison with both TiC-Onco, Khorana showed a higher specificity (69 i 5 82, TiC-Onco versus Khorana, respectively, p<0.001. Nevertheless, it is reasonable to think that higher sensitivity is more desirable as the test is used to identify a serious and deathly but preventable disease such as VTE in cancer patients.

If a similar specificity to those showed by Khorana were desired, we have chosen another cut-off for TiC-Onco resulting in a specificity of 80% being TiC-Onco significantly better than Khorana in all the parameters analysed but, logically, the specificity and NPV.

Clinicians are very much interested in knowing that TiC-Onco is more accurate than the Khorana test in the identification of cancer patients at high risk for VTE. That means that the thrombo-prophylaxis guided by Ti C-Onco will be more efficacious because it will be given to those patients who most need it as demonstrated by the lower NNT when TiC-Onco is used, decreasing the risk of unjustified haemorrhage.

In summary, we have developed a risk score that is significantly better than the Khorana score to identify the cancer patients in an outpatient or also clinical setting at high risk for developing VTE. Patients identified as at high risk for VTE with this new risk score would have a greater benefit from thrombo-prophylaxis despite the risk they may have for haemorrhage and are candidates to receive a prophylactic treatment to prevent the development of VTE. It is very important to use more accurate tests like TiC-Onco to identify patients at risk of VTE who would benefit from thrombo-prophylaxis since we have effective drugs to prevent VTE and cancer patients with VTE have a higher rate of death than cancer patients without VTE (31%, versus 11.25%, p<0.001). We have developed a preferred combination of predictive markers, optionally further to be used with the above function 1. TiC-Onco for the identification of patients at high risk of developing a cancer associated VTE. As the risk of cancer associated VTE is high even 6 months before cancer diagnosis and the peak of the incidence is from 0 to 6 months post diagnosis, it should be recommended to use TiC-Onco at the moment a cancer is suspected in a patient.

As strengths of our study it can be summarized that the present study is a multi-location study, with a large portion of patients in advanced stages of TNM and that we have performed a sub-analysis in post-chemotherapy VTE cases. It is also a relevant strength that significantly better results are obtained based on TiC-Onco in comparison to Khorana, especially when analysing those classification functions such as sensitivity, specificity, positive and negative likelihood ratios more strongly associated with the capacity of the test than with the specific characteristics of the population in which it is tested.

Relevance from the clinical point of view

Our results suggest some conclusions very relevant from the clinical point of view:

1) The better discrimination of TiC-Onco over the Khorana Score. That means that by using TiC-Onco we would have a better ability to discriminate between the cancer patients who will develop a VTE close to the diagnostis of cancer, from the diagnosis of cancer to initiation of chemotherapy.

2) TiC-Onco has high sensitivity to identify most (70-79%) of the cancer patients who will develop VTE.

3) TiC-Onco has high specificity to identify most (69-73%) of the cancer patients who will NOT develop VTE.

4) For the same specificity as that showed by the Khorana score, TiC-Onco was significantly better in all the parameters analysed when compared to the Khorana score.

5) Using TiC-Onco we could identify a very significant number of false negatives produced by the Khorana score (65-72%).

6) Using TiC-Onco we could be more efficacious in treatment because we would need to treat less patients in order to avoid one VTE than in the case if we were using Khorana.

7) TiC-Onco is superior to Khorana both to confirm the existence of a high risk to develop VTE as well as to confirm the absence of risk to develop VTE.

8) We have developed a risk score that is significantly better than the Khorana score to identify the cancer patients in outpatient setting at high risk for developing VTE. TiC- Onco should be used preferably at the moment a cancer is suspected. References

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Claims

1. A method for the thromboembolic event risk assessment in a subject suffering from cancer comprising the steps of determining in a sample isolated from said subject the presence of at least one allele in all of rs2232698, rs5985, rs6025 and rs4524, namely Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), factor XIII Val34Leu (rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524), whereby said presence is indicative of the risk of suffering a thromboembolic event (vein thrombosis, deep vein thrombosis and/or pulmonary embolism) and/or a recurrent thromboembolic event.

2. The method as defined in claim 1 wherein the thromboembolic disease is selected from the group of fatal or non-fatal myocardial infarction, stroke, transient, ischemic attacks, peripheral arterial disease, vein thrombosis, deep vein thrombosis, pulmonary embolism or a combination thereof, preferably from venous

thromboembolism, deep vein thrombosis and pulmonary embolism.

3. A method for identifying a subject suffering from cancer in need of anticoagulant and/or antithrombotic therapy or in need of prophylactic antithrombotic and/or anticoagulant therapy comprising the steps of determining in a sample isolated from said subject the presence in at least one allele of polymorphisms rs2232698, rs5985, rs6025 and rs4524, namely Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), factor XIII Val34Leu (rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524), whereby said presence is indicative of having a decreased response to an antithrombotic and/or anticoagulant therapy and of being in need of early and aggressive antithrombotic and/or anticoagulant therapy or in need of prophylactic antithrombotic and/or anticoagulant treatment.

4. The method as defined in any of claims 1 to 3 further comprising determining one or more risk factor(s) selected from the group consisting of body mass index (BMI), primary site of the tumor, tumor stage, family history of VTE, or additionally personal history of VTE, previous surgery, use of a central or peripheral catheter,

chemotherapy, D-dimer, soluble p-selectin or additionally age, race, sex, smoking status, systolic blood pressure, diastolic blood pressure, hospitalization, plaster case, immobilization, surgery, trauma, hormonal contraceptive or hormone therapy, pregnancy, prolonged travel (>2 hours), collagen vascular diseases, heart failure, further medications, nephrotic syndrome, diabetes mellitus, low density lipoprotein (LDL)-cholesterol level, high density lipoprotein (HDL)-cholesterol level, cholesterol level, triglyceride levels, pregnancy, or Khorana score.

5. The method according to any of the claims 1 to 4 wherein the method is performed in a subject during the procedure to identify whether the patient is suffering from cancer and/or during the procedure to characterize the TNM stage of the cancer.

6. The method according to any of the claims 1 to 4 wherein the x method is performed in a subject at any time from the diagnosis of the cancer.

7. The method according to any of the claims 1 to 6 wherein the method is performed in a subject suffering from cancer and treated in an out-patient setting.

8. The method according to any of claims 1 to 7, wherein the sample is an oral tissue sample, scraping or wash or a biological fluid sample, preferably saliva, urine or blood, or buccal cells.

9. The method according to any one or more of claims 1 to 8, wherein the presence or absence of the genetic variant is identified by amplifying or failing to amplify an amplification product from the sample, wherein the amplification product is preferably digested with a restriction enzyme before analysis and/or wherein the genetic variant is identified by hybridizing the nucleic acid sample with a primer label which is a detectable moiety.

10. A method of determining the probability of an individual suffering from cancer of presenting a thromboembolism disease or event or a recurrent thromboembolism disease or event based on the presence of 1 to P classical risk factors and 1 to J polymorphisms selected from the group of rs2232698, rs5985, rs6025 and rs4524, namely Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), factor XIII Val34Leu (rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524), using the formula:

Probability (Y=llXi, X_n) = 1/ 1 + exp (β₀ + βι Xi + ... + β_η X_n + _f._g x_rX_g +....β_Ν χ_ή·_Χί), wherein:

Probability (Y = 1 1 xi. Xn) = probability of presenting a thrombosis in a particular Cancer patient - with concrete and measurable characteristics in a number of variables 1, n,

- Exp = exponential natural base;

- β₀ = coefficient that defines the risk (the probability) of thrombosis non related with the variables 1 to n,

- βι = regression coefficient that expresses the risk (higher or lower) to present thrombosis associated with the value/presence of the predictor variable XI,

- xi = value taken by the predictor variable xl in an individual,

M β_η = regression coefficient that expresses the risk (higher or lower) to present thrombosis associated with the value/presence of the predictor variable X_n,

- X_n = value taken by the predictor variable X_n in an individual,

and

P_f.g = regression coefficient that expresses the risk (higher or lower) to present thrombosis associated with the combined presence of the predictor variables Xf and

X_f = value taken by the predictor variable x, in an individual,

- X_g = value taken by the predictor variable X_f in an individual, - h i = regression coefficient that expresses the risk (higher or lower) to present thrombosis associated with the combined presence of the predictor variables X and Xi,

- X = value taken by the predictor varible X in an individual,

- Xi = value taken by the predictor variable x, in an individual.

11. A computer program or a computer-readable media containing means for carrying out a method as defined in any of claims 1 to 10.

12. A kit comprising reagents for detecting the identity of all the nucleotides of the group of rs2232698, rs5985, rs6025 and rs4524, namely Serpin A10 (protein Z inhibitor) Arg67Stop (rs2232698), factor XIII Val34Leu (rs5985), factor V Leiden Arg506Gln (rs6025), and factor V K858R (rs4524).

13. The method according to any of the claims 4 to 10, wherein the risk factors to be

determined as predictive variables are BMI, primary site of the tumor, tumor stage, family history of VTE, preferably included in function 1.

14. The method of claim 12, wherein the sample is from a patient suffering from cancer.

15. The kit according to any one of claims 12 or 14, wherein means to determine the risk factors of claim 13 are included.