CN1973778A - Method of predicting serious complication risk degree after gastric cancer operation - Google Patents
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Abstract
The present invention is objective, quantitative and precise method of predicting serious complication risk degree after gastric cancer operation. The method includes the following steps: 1. screening out factors affecting the serious complication after gastric cancer operation through overall single factor analysis; 2. determining the prognostic determining factor through two-value multiple non-conditional logic regression analysis; 3. determining the optimal prediction value dividing value through the work characteristic analysis on the testee; and 4. establishing the predicting model with main risk factor as the independent variable and judging the serious complication risk degree after gastric cancer operation by means of the prediction probability. The present invention is one objective and quantitative intelligent risk evaluation system.
Description
One, technical field
The present invention relates to a kind of Forecasting Methodology that is used for medical science, be specifically related to a kind of method of coming serious complication risk degree behind the predicting surgical by information, operation information, tumor pathological information before the Patients with Gastric Cancer art.
Two, background technology
In China, gastric cancer is one of modal malignant tumor, and its sickness rate and mortality rate all occupy various malignant tumor prostatitis.The main Therapeutic Method of gastric cancer is surgical operation and adjuvant chemotherapy, and the operation of radical-ability gastric cancer is to reach unique Therapeutic Method of curing purpose at present.The gastric cancer radical operation of standard comprises stomach excision, lymph node dissection and 3 contents of reconstruction of digestive tract, operation wound is big, complicated operation, because the patients with gastric cancer of China mostly is the old people, chronic comorbidities is often arranged, tumor is seen so that the middle and advanced stage cancer comparatively more again, so even in the abundant large-scale medical institutions of surgical experience, the incidence rate of postoperative gastric cancer severe complication still reaches 10%～20%.Common postoperative gastric cancer severe complication is as follows: (one) severe infections comprises thoracic cavity infection, abdominal cavity infection, infection of incisional wound etc.; (2) intestinal obstruction comprises acute afferent loop obstruction, anastomotic block, efferent loop obstruction, stomach paralysis etc.; (3) fistula comprises pancreas fistula, fistula of operative incision, duodenum stump fistula etc.; (4) multiple organ dysfunction comprises organ failures such as the heart, lung, liver, kidney, stress ulcer, DIC etc.Compare with other operations, the severe postoperative complication of gastric cancer has more its uniqueness and complexity, in case take place, Clinical Processing is very thorny, and medical expense is costly, and serious symptom person is secondary multiple organ dysfunction syndrome and threat to life very easily, and case fatality rate is up to 24%.Therefore, determine the risk factor and the risk of severe complication behind the radical operation for carcinoma of stomach, have crucial clinical value and social value.
Determine to reach the research field of risk profile at the risks and assumptions of postoperative gastric cancer severe complication, present domestic and international research still exists many defectives: the virulence factor that the researcher that (1) has is gathered is few, the participation case is few, do not meet one of core requirement of modern evidence-based medicine EBM, promptly clinical evidence will be estimated (systematic review) and meta-analysis (meta-analysis) from random contrast clinical trial (RCT), the systematicness of multicenter, large sample; (2) researcher that has adopts the single factor analysis method, and the relation between postoperative gastric cancer severe complication and the numerous virulence factor is very complicated, single factor analysis can't be in the relation of complexity the effect of the multiple Confounding Factor of balance, also can't form forecast model; (3) researcher that has adopts the multiple linear regression analysis method, can't determine the best cut off value of prediction probability, can't verify accurately and estimates practicality and poor operability the model of setting up; In fact and non-linear relation and the relation between severe postoperative complication and the various virulence factor, simultaneously, a good forecast model, must determine the best cut off value of prediction probability, must be by strict checking, prove that it has higher accuracy, sensitivity, specificity, and require easy and simple to handle, practical; (4) desire to find out the influential numerous factors of severe postoperative complication the effect significant factor, to reach the purpose of disease prognosis prediction, must do further to expand to traditional Forecasting Methodology, the knowledge in statistics forward position and thought are incorporated among the analytical method of data.
Three, summary of the invention
The object of the present invention is to provide a kind of Forecasting Methodology of serious complication risk degree after gastric cancer operation.The present invention is by clinical indices such as information, operation information, tumor pathological information before the Patients with Gastric Cancer art being carried out careful Retrospective review comprehensively, returning (Logistic Regression) by the polynary non-conditional logic of two-value analyzes, determine the main hazard factor of postoperative gastric cancer severe complication, calculate its relative risk; Analyze by experimenter's performance curve (ROC), determine the optimum prediction cut off value, estimate sensitivity, the specificity of this Forecasting Methodology; Foundation is the forecast model of independent variable with the main hazard factor, thereby for the assessment of severe postoperative complication risk provides objective basis, reaches and help patient to carry out medical decision making, auxiliary ward management, instruct effect such as medicine clinical research.
For realizing purpose of the present invention, the invention provides a kind of method of utilizing polynary non-conditional logic recurrence (LogisticRegression) analytical technology of two-value and experimenter's performance curve (ROC) analytical technology to assess serious complication risk degree after gastric cancer operation, this Forecasting Methodology may further comprise the steps:
1. use SPSS 13.0 software kits and set up the gastric cancer information database, 79 variable indexs that write down are as follows: (1) continuous variable: time, diameter of tumor, age, plasma albumin, prealbumin, liver function Child-pugh scoring, total bilirubin, hemoglobin, numeration of leukocyte, lymphocyte count, prothrombin time, blood glucose, carcinoembryonic antigen in transfusion volume, the art in lymphatic metastasis number, lymph node dissection number, the art; (2) orderly variable: lymph node (LN) cleaning degree, surgical radical treatment degree, T by stages, N by stages, TNM by stages, tumor differentiation degree, Borrman typing; (3) two classified variables: the 10th group of LN cleaning, 11p group LN cleaning, the 12nd group of LN cleaning, the 13rd group of LN cleaning, 14a group LN cleaning, 14v group LN cleaning, the 15th group of LN cleaning, 16a group LN cleaning, 16b group LN cleaning, the excision of associating internal organs, the associating lobectomy of liver, the associating gallbladder removal, the associating splenectomy, associating body of pancreas tail and splenectomy, associating Whipple operation, associating oophorectomize, the excision of associating transverse colon, associating lifting colectomy, residual stomach excision, the jejunal nutrition fistulation, Broun coincide, soak into peripheral organs, soak into omentum majus, soak into liver, soak into gallbladder, soak into transverse mesocolon, soak into transverse colon, soak into head of pancreas, soak into the body of pancreas tail, soak into spleen, soak into esophagus, soak into duodenum, distant metastasis of human, hepatic metastases, peritoneum shifts, ovarian metastasis, extensively lymphatic metastasis, extensively shift in the abdominal cavity, ascites, before the art and deposit coronary heart disease, severe arrhythmia, hypertension, chronic obstructive pulmonary disease, chronic renal insufficiency, liver cirrhosis, portal hypertension, cerebrovascular, diabetes, lose weight, pyloric obstruction, give nutritional support before the art, postoperative gives nutritional support etc.; (4) nominal variable (need carry out the dummy argument processing, change two classified variables into): reconstruction of digestive tract mode, stomach excision extension, tumor locus, types of organization;
2. earlier 79 variable indexs being investigated are carried out single factor analysis, corresponding statistical procedures method is as follows: the continuous variable adopts independent sample T check; Variable adopts non parametric tests (Mann-Whitney U check or Kolmogorov-Smirnov Z test) in order; Two classified variables adopt X 2 test or the accurate probabilistic method of Fisher; (CI) gets 95% in the credibility interval, significant difference is got P≤0.05, and the result filters out 18 difference has the variable index of statistical significance as follows: chronic comorbidities, portal hypertension, total gastrectomy, pyloric obstruction, Nol6a group lymph node dissection, No13 group lymph node dissection, tumor TNM are by stages before time, liver function Child-Pugh integration, the art in blood loss, age, diameter of tumor, the art in associating body of pancreas tail and splenectomy, associating Whipple operation, Borrman typing, the art, lymph node dissection degree, residual stomach excise, prothrombin time;
3. 18 variablees that will filter out are done the polynary non-conditional logic regression analysis of two-value, carry out model testing, discriminant analysis, calculate the partial regression coefficient and the relative risk of each factor: OR=Exp (B), it is as follows to draw 8 factors that really influence the postoperative gastric cancer severe complication: blood loss, tumor TNM are by stages in associating body of pancreas tail and splenectomy, lymph node dissection degree, liver function Child-Pugh integration, the preceding chronic comorbidities of art, total gastrectomy, No16a group lymph node dissection, the art;
4. adding up every patient's post-operative complication, actual a situation arises and prediction probability, with the prediction probability is test variable, a situation arises with post-operative complication reality is state variable, do experimenter's performance curve (ROC) analysis, estimate the value of this Forecasting Methodology according to area under curve (Az), determine the optimum prediction cut off value according to stepping on (Youden) index especially, and estimate sensitivity, the specificity of this Forecasting Methodology;
5. according to the logistic regression analysis result of above-mentioned steps 3, set up the forecast model of serious complication risk degree after gastric cancer operation: P=Exp ∑ B0+B1X1+ ... + BkXk/1+Exp ∑ B0+B1X1+ ... + BkXk, wherein P is a dependent variable, represent the risk probability value, X is an independent variable, represents each risk factor, and B is a partial regression coefficient, in conjunction with the best cut off value of determining by outstanding mounting index, promptly can be used for predicting the risk probability of every routine Patients with Gastric Cancer generation severe postoperative complication.
Beneficial effect of the present invention is as follows:
In medical practice, the result of the numerous often paathogenic factor comprehensive functions of the generation of a certain disease, cause effect relation wherein is intricate.Logistic regression (Logistic Regression) is when approximating method carries out multivariate analysis, can be in the relation of complexity the effect of the multiple Confounding Factor of balance, the factor that filters out is more objective and credible, being particularly useful for dependent variable is that two classified variables, independent variable are the clinical data of a plurality of risk factors, and this analytical method limits seldom the distributivity of data, and clinical use is particularly convenient.
Experimenter's performance curve (Receiver Operating Characteristic Curve, ROC) analytical method is that sensitivity during with different cut off value and (1-specificity) are respectively as vertical coordinate and abscissa, a curve that draws, can estimate the predictive ability of this prognoses system by the measuring and calculating area under a curve, and can determine the prediction cut off value of the best that sensitivity and specificity are all higher according to stepping on (Youden) index especially.
The variable index of this forecast model all is highly objective Clinical Laboratory, iconography, operation, pathology index, so reliability is extremely strong; Analyze by degree of fitting check (Goodness of fit test) and ROC, confirm that this forecast model has accuracy, sensitivity, the specificity of height.
This forecast model carries out quantitative analysis by the risk to the postoperative gastric cancer severe complication, helps patient to carry out medical decision making, auxiliary ward management, instructs effect such as medicine clinical research thereby reach; Simultaneously, this cover operation risk appraisal procedure and method for establishing model also can be widely used in other operations except that gastric cancer.
Help patient to carry out medical decision making: evidence-based medicine EBM pattern (Evidence-based medicine, EBM) be the core schema of current clinical medicine practice and research, one of three big basic principles of evidence-based medicine EBM are exactly as one of the Primary Actor of medical practice and policymaker with the patient.The enforcement of any diagnosis and treatment decision-making of doctor all must obtain patient's understanding and acceptance, all must consider expected degree and the ability to shoulder economically of patient to this Therapeutic Method.In clinical practice, it is to produce little effect that some patient's operation is doomed, and because the generation of severe postoperative complication, makes the quality of life extreme difference, and final death is still inevitable, has both increased the weight of patient's misery, has caused serious medical treatment waste again.This forecast model can help patient to participate in the medical decision making that whether undergos surgery by the objective prediction to the operation prognosis.
Auxiliary ward management: whether this forecast model of postoperative care rank of (1) decision patient enters intensive care unit(ICU) (ICU) to the decision patient unique effect.According to statistics, among at present domestic patient ICU, the patient that the reality of low danger need not enter ICU accounts for 30%.This forecast model can help to determine by differentiating low danger of postoperative and high risk patient whether patient needs Intensive Care Therapy, and in the ward the needed nurse of per tour and each patient need the nursing grade.In medical expense more and more expensive epoch of Intensive Care Therapy medical expense particularly, this prognoses system can significantly alleviate patient's financial burden, and saves medical resource; (2) in current medical present situation, doctor-patient dispute increases sharply, and partly cause is that the doctor lacks objective, quantification, Forecasting Methodology that accuracy is high to the risk of operation, makes patient produce too high expectation to surgical effect; By the operation risk prognoses system, it is dangerous to help patient correctly to be familiar with its operation, helps to alleviate conflict between doctors and patients, reduces medical tangle; (3) estimate treatment level between different medical mechanism, the different treatment group, analyze the Limited resources utilization ratio, and even determine annual health financial budget etc.
Instruct medicine clinical research, be used to estimate new medical procedure: illustrate, we choose mortality rate behind the predicting surgical is that 50～60% patient is divided into two groups, one group by conventional process, another group gives the postoperative EEN and supports (EN) except that conventional process, found that the actual of one group of back reduces to 30%, this shows that EN can obviously reduce the postoperative death rate, is worthy to be popularized.
Four, description of drawings
Fig. 1 is experimenter's performance curve (ROC curve) of this Forecasting Methodology.
Five, the specific embodiment:
Embodiment 1: the Forecasting Methodology of serious complication risk degree after gastric cancer operation, and its method step is as follows:
1. the foundation of gastric cancer information database:
1.1 clinical data source:
Object of study derive from June, 2002～2006 year year in June in the Jiangsu Prov. People's Hospital, the patient of drum tower hospital of Nanjing University, Nanjing Military Command hospital general row gastric cancer operation totally 1542 examples.Adopt retrospective case one contrast research method, the severe complication person takes place for the operation back in the case group, and matched group then derives from the gastric cancer surgical patient of the no severe complication of being in hospital the same period.
1.2 all clinical data information of investigation content are as the criterion with original medical history record, adopt unified variable index, all input is with the gastric cancer information database of SPSS13.0 statistical package foundation.In physical examination information, lab testing information, imaging examination information, operation information, tumor pathological information, choose 79 indexs altogether and analyze, comprising: (1) continuous variable: time, diameter of tumor, age, plasma albumin, prealbumin, liver function Child-pugh scoring, total bilirubin, hemoglobin, numeration of leukocyte, lymphocyte count, prothrombin time, blood glucose, carcinoembryonic antigen in transfusion volume, the art in lymphatic metastasis number, lymph node dissection number, the art as possible risks and assumptions; (2) orderly variable: lymph node (LN) cleaning degree, surgical radical treatment degree, T by stages, N by stages, TNM by stages, tumor differentiation degree, Borrman typing; The grade scale of variable sees Table 1 in order; (3) two classified variables: the 10th group of LN cleaning, 11p group LN cleaning, the 12nd group of LN cleaning, the 13rd group of LN cleaning, 14a group LN cleaning, 14v group LN cleaning, the 15th group of LN cleaning, 16a group LN cleaning, 16b group LN cleaning, the excision of associating internal organs, the associating lobectomy of liver, the associating gallbladder removal, the associating splenectomy, associating body of pancreas tail and splenectomy, associating Whipple operation, associating oophorectomize, the excision of associating transverse colon, associating lifting colectomy, residual stomach excision, the jejunal nutrition fistulation, Broun coincide, soak into peripheral organs, soak into omentum majus, soak into liver, soak into gallbladder, soak into transverse mesocolon, soak into transverse colon, soak into head of pancreas, soak into the body of pancreas tail, soak into spleen, soak into esophagus, soak into duodenum, distant metastasis of human, hepatic metastases, peritoneum shifts, ovarian metastasis, extensively lymphatic metastasis, extensively shift in the abdominal cavity, ascites, before the art and deposit coronary heart disease, severe arrhythmia, hypertension, chronic obstructive pulmonary disease, chronic renal insufficiency, liver cirrhosis, portal hypertension, cerebrovascular, diabetes, lose weight, pyloric obstruction, give nutritional support before the art, postoperative gives nutritional support etc.; (4) nominal variable: reconstruction of digestive tract mode, stomach excision extension, tumor locus, types of organization etc.For nominal variable, need carry out the dummy argument processing, be converted into a plurality of two classified variables.Check that then to investigate synteny, there is serious synteny in the multivariate correlation matrix as showing on evidence, then carry out variable deletion.
Table 1 is the grade scale (part) of variable in order
| Variable (X) | Scoring | Analytical standard | Variable (X) | Scoring | Analytical standard |
| Sex stomach excision mode method of alimentary tract reconstruction cancer of the stomach Borrman somatotype | 0 1 1 2 3 4 5 1 2 3 1 2 3 4 | The residual stomach Bi Luo of the full stomach associating internal organs of men and women's orifice of the stomach side lateral pylorus-I Bi Luo-II Roux-en-Y Bor-I Bor-II Bor-III BorIV | Liver function classification knub position TNM by stages | 1 2 3 1 2 3 1 2 3 4 5 6 | The full stomach IA of Child-A Child-B Child-C distal stomach proximal gastric IB II IIIA IIIB IV |
1.3 the diagnostic criteria of severe postoperative complication is with a situation arises:
The severe postoperative complication is defined as the complication that potential life danger is arranged that takes place in the postoperative 30 days, comprising: need the postoperative hemorrhage, pulmonary infection, intestinal fistula, heart failure, acute renal failure of operation once more etc.; Surgical death is defined as the death of any reason in the postoperative 30 days.
The severe complication incidence rate is 17.6% (271/1542) behind this group radical operation for carcinoma of stomach, occurrence frequency is followed successively by thoracic cavity infection and hydrothorax, abdominal cavity infection, dynamic ileus, infection of incisional wound, the pancreas fistula, fistula of operative incision, disruption of wound, acute afferent loop obstruction, duodenum stump fistula, intraperitoneal hemorrhage, anastomotic block, multiple organ dysfunction (comprises the heart, lung, liver, organ dysfunctions such as kidney are incomplete), stress ulcer, the stomach paralysis, acute pancreatitis, the abdominal cavity lymphatic fistula, acute cholecystitis etc., multiple severe complication can appear in some patient, and operative mortality is 1.4% (21/1542).
2. single factor analysis:
Selected 79 variablees are made single factor analysis, the continuous variable adopts independent sample T check, variable adopts non parametric tests (Mann-Whitney U check or Kolmogorov-Smirnov Z test) in order, two classified variables adopt X 2 test or the accurate probabilistic method of Fisher, the credibility interval gets 95%, and significant difference is got P≤0.05.Statistical result (sees Table 2 respectively, table 3, table 4) show: severe complication is closely related after in 79 factors being analyzed 18 factors and radical operation for carcinoma of stomach being arranged, and is respectively associating body of pancreas tail and splenectomy, associating Whipple operation, the Borrman typing, blood loss in the art, age, diameter of tumor, time in the art, liver function Child-Pugh integration, chronic comorbidities before the art, portal hypertension, total gastrectomy, pyloric obstruction, No16a organizes lymph node dissection, No13 organizes lymph node dissection, tumor TNM by stages, the lymph node dissection degree, residual stomach excision, prothrombin time.
Table 2 continuous variable statistical result
| Correlative factor | No complication group | The complication group is arranged | The P value |
| Time in blood loss (ml) art in age (year) diameter of tumor (cm) art (hour) Child-pugh integration prothrombin time (second) | 57.87±13.168 5.015±2.6005 232.05±189.650 3.316±0.7894 5.17±0.445 11.684±1.7919 | 62.13±12.912 6.184±3.4508 395.33±270.351 3.754±1.1480 6.52±0.894 13.892±1.8415 | 0.013 0.018 0.001 0.025 0.009 0.012 |
Table 3 two classified variable statistical results
| Correlative factor | No complication group | The complication group is arranged | The P value | |
| The residual stomach excision of chronic comorbidities portal hypertension total gastrectomy associating Whipple operation pyloric stenosis No.16a group lymph node dissection No.13 group lymph node dissection associating body of pancreas tail and splenectomy before the art | (-) (+) (-) (+) (-) (+) (-) (+) (-) (+) (-) (+) (-) (+) (-) (+) (-) (+) | 995 276 1235 36 1232 39 1106 165 1250 21 1170 101 995 276 976 295 1219 52 | 159 112 240 31 243 28 190 81 253 18 232 39 133 138 145 126 238 33 | 0.000 0.020 0.035 0.014 0.009 0.031 0.004 0.002 0.000 |
The non parametric tests result of table 4 ranked data
| Correlative factor | Wilcoxon W | The Z value | The P value |
| Lymph node dissection degree (0-D0,1-D1,2-D2,3-D3,4-D4) TNM (1-IA by stages, 2-IB, 3-II, 4-IIIA, 5-IIIB, 6-IV) advanced gastric carcinoma Borrman typing (1-Bor I, 2-BorII, 3-BorIII, 4-BorIV) | 26597.000 103559.500 103410.500 | -1.337 -2.633 -3.073 | 0.002 0.028 0.016 |
3. the polynary non-conditional logic regression analysis of two-value
18 variablees that Preliminary screening goes out are done the polynary non-conditional logic regression analysis of two-value (retreating method), carry out model testing, discriminant analysis is calculated the partial regression coefficient and the relative risk of each factor: OR=Exp (B).The result shows, have 8 factors and enter Logic Regression Models, be followed successively by: blood loss (OR=1.207), tumor TNM (OR=1.119) (table 8) by stages in chronic comorbidities (OR=1.961), total gastrectomy (OR=1.501), 16a group lymph node dissection (OR=1.391), the art before associating body of pancreas tail and splenectomy (OR=3.422), lymph node dissection degree (OR=2.967), liver function Child-Pugh integration (OR=2.012), the art by the effect power.Model testing result (table 5,6) shows: regression equation has the significance meaning; Differentiating assay (table 7) shows: model has higher predictablity rate (85.1%).
Table 5 model testing 1 (degree of fitting check)
| Chi-square | df | Sig. | ||
| Step 1 | Step Block Model | 357.948 357.948 357.948 | 34 34 34 | .000 .000 .000 |
Table 6 model testing 2
| -2Log Likelihood | Cox & Snell R Square | Nagelkerke R Square | |
| Step 1 | 205.037 | .572 | .776 |
Table 7 is differentiated check table
| The actual example that takes place | The model prediction example | Add up to | Accuracy rate (%) | |
| + | - | |||
| + | 209 | 62 | 271 | |
| - | 168 | 1103 | 1271 | |
| Add up to | 377 | 1165 | 1542 | 85.1 |
The polynary non-conditional logic regression analysis result of table 8 two-value
| Independent variable (X) | Regression coefficient (B) | Standard deviation (S.E.) | Wald value (Wald) | df | P value (Sig) | Relative risk (OR) | 95.0％CI for OR | |
| Lower | Unner | |||||||
| 1. chronic comorbidities 5. total gastrectomy 6.No16a organize by stages 9. constants of lymph node dissection 7. intraoperative blood loss amounts 8. tumour TNM before associating body of pancreas tail and splenectomy 2. lymph node dissection degree 3. liver function Child-Pugh integrations 4. arts | 1.230 0.021 0.009 1.041 0.892 0.804 0.003 0.016 -2.942 | 0.741 0.015 0.010 0.426 0.470 0.563 0.097 0.180 0.327 | 2.753 1.107 0.018 2.435 3.139 1.943 0.012 0.009 1.357 | 1 1 1 1 1 1 1 1 1 | 0.012 0.015 0.029 0.034 0.056 0.103 0.149 0.288 0.043 | 3.422 2.967 2.012 1.961 1.501 1.391 1.207 1.119 0.813 | 0.800 0.986 0.989 0.907 0.915 0.727 0.718 0.649 | 14.637 14.012 13.762 7.974 5.785 6.603 6.762 5.230 |
4. experimenter's performance curve (ROC) is analyzed
Adding up every patient's post-operative complication, actual a situation arises and prediction probability, is test variable with the prediction probability, and actual a situation arises is state variable with post-operative complication, does the analysis of experimenter's performance curve, obtains area under curve (Az); Especially step on (Youden) index=sensitivity+specificity-1, with the best cut off value that a bit is judged to prediction probability of outstanding mounting index maximum, the result is shown in figure one and table 9:
ROC area under curve (Az) is 83.3%, shows that forecast model has good predictive value (when Az was 0.5～0.6, the expression predictive value was low, and Az is, the expression predictive value is medium, and Az is 0.8～1.0, expression predictive value height) at 0.6～0.8 o'clock; The marginal value (P) corresponding with outstanding mounting index maximum point is 0.391 and (promptly is judged to postoperative when P＜0.391 and will severe complication can not take place, when P＞0.391, be judged to postoperative severe complication will take place), at this moment, the sensitivity of prediction is 85.7%, and specificity is 78.6%.
Table 9 is judged optimum prediction probability cut off value according to outstanding mounting index
| The prediction probability value | Sensitivity | The 1-specificity | Outstanding mounting index |
| 0.000 0.019 0.027 ...... 0.302 0.338 0.391* 0.445 0.479 ...... 0.913 0.976 1.000 | 1.000 1.000 1.000 ...... 0.909 0.879 0.857* 0.803 0.673 ...... 0.166 0.015 0.000 | 1.000 0.971 0.941 ...... 0.559 0.391 0.214* 0.205 0.195 ...... 0.029 0.000 0.000 | 0.000 0.029 0.059 ...... 0.350 0.488 0.643* 0.598 0.478 ...... 0.137 0.015 0.000 |
The relation (seeing Table 10) of further analyses and prediction probability grade and severe postoperative complication degree, the result confirms: prediction probability (P value) grade is higher, and severe postoperative complication degree more weighs, i.e. risk higher (P＜0.001).
The relation of table 10 model probability grade and severe postoperative complication degree
| The P value | Severe postoperative complication degree | Add up to | Coefficient of contingency | ||||
| (1) | (2) | (3) | (4) | ||||
| Danger is high-risk in the low danger | 0.4～0.6 0.6～0.8 0.8～1.0 | 31 19 6 | 23 38 25 | 18 31 29 | 4 16 31 | 76 104 91 | 0.434 P＜0.001 |
5. set up the forecast model of the serious serious complication risk degree of postoperative gastric cancer
According to the polynary non-conditional logic regression analysis result of the two-value in the above-mentioned steps 3, it is as follows to set up forecast model: P (1)=Exp ∑ (2.942+1.23X1+0.021X2+0.009X3+1.041X4+0.892X5+0.804X6+0.0 03X7+0.016X8)/[1+Exp ∑ (2.942+1.23X1+0.021X2+0.009X3+1.041X4+0.892X5+0.804X6+0.0 03X7+0.016X8)], and setting the prediction probability cut off value is 0.391; Being judged to postoperative when P＜0.391 will severe complication can not take place, and be judged to postoperative when P＞0.391 severe complication will take place, and the P value is big more, and the probability that severe complication takes place is big more.
The present invention is further illustrated below by concrete case:
The relevant information of certain Patients with Gastric Cancer is as follows: according to the state of an illness, he (she) needs to implement radical-ability total gastrectomy (X5=1), associating body of pancreas tail and splenectomy (X1=1), the lymph node dissection degree is D3 (X2=3), it (is that No.16a group lymph node need clean that the ventral aorta peripheral lymph node is cleaned up, X6=1), liver function Child-Pugh scoring is 5 minutes (X3=5) before its art, pathologic stages of tumour is IIIA phase (X8=4), as there is not a chronic comorbidities (X4=0) before the art, blood loss is expected to be 200ml (X7=200) in the art, and the substitution predictive equation draws P=0.680, because P＞0.391, so the severe postoperative complication might take place this patient of prediction, 0.6＜P＜0.8 shows that its risk factor that severe complication takes place is medium.
Claims (1)
1. the Forecasting Methodology of a serious complication risk degree after gastric cancer operation, it is characterized in that this method is to utilize the polynary non-conditional logic regression analysis technology of two-value and experimenter's performance curve analytical technology to assess the risk of postoperative gastric cancer severe complication, this Forecasting Methodology may further comprise the steps:
(1) use SPSS 13.0 software kits and set up the gastric cancer information database, 79 variable indexs that write down are as follows: (1) continuous variable: time, diameter of tumor, age, plasma albumin, prealbumin, liver function Child-pugh scoring, total bilirubin, hemoglobin, numeration of leukocyte, lymphocyte count, prothrombin time, blood glucose, carcinoembryonic antigen in transfusion volume, the art in lymphatic metastasis number, lymph node dissection number, the art; (2) orderly variable: lymph node (LN) cleaning degree, surgical radical treatment degree, T by stages, N by stages, TNM by stages, tumor differentiation degree, Borrman typing; (3) two classified variables: the 10th group of LN cleaning, 11p group LN cleaning, the 12nd group of LN cleaning, the 13rd group of LN cleaning, 14a group LN cleaning, 14v group LN cleaning, the 15th group of LN cleaning, 16a group LN cleaning, 16b group LN cleaning, the excision of associating internal organs, the associating lobectomy of liver, the associating gallbladder removal, the associating splenectomy, associating body of pancreas tail and splenectomy, associating Whipple operation, associating oophorectomize, the excision of associating transverse colon, associating lifting colectomy, residual stomach excision, the jejunal nutrition fistulation, Broun coincide, soak into peripheral organs, soak into omentum majus, soak into liver, soak into gallbladder, soak into transverse mesocolon, soak into transverse colon, soak into head of pancreas, soak into the body of pancreas tail, soak into spleen, soak into esophagus, soak into duodenum, distant metastasis of human, hepatic metastases, peritoneum shifts, ovarian metastasis, extensively lymphatic metastasis, extensively shift in the abdominal cavity, ascites, before the art and deposit coronary heart disease, severe arrhythmia, hypertension, chronic obstructive pulmonary disease, chronic renal insufficiency, liver cirrhosis, portal hypertension, cerebrovascular, diabetes, lose weight, pyloric obstruction, give nutritional support before the art, postoperative gives nutritional support etc.; (4) nominal variable need carry out the dummy argument processing, changes two classified variables into: reconstruction of digestive tract mode, stomach excision extension, tumor locus, types of organization;
(2) earlier 79 variable indexs being investigated are carried out single factor analysis, corresponding statistical procedures method is as follows: the continuous variable adopts independent sample T check; Variable adopts non parametric tests in order, i.e. Mann-Whitney U check or Kolmogorov-Smirnov Z test; Two classified variables adopt X 2 test or the accurate probabilistic method of Fisher; (CI) gets 95% in the credibility interval, significant difference is got P≤0.05, and the result filters out 18 difference has the variable index of statistical significance as follows: chronic comorbidities, portal hypertension, total gastrectomy, pyloric obstruction, No16a group lymph node dissection, No13 group lymph node dissection, tumor TNM are by stages before time, liver function Child-Pugh integration, the art in blood loss, age, diameter of tumor, the art in associating body of pancreas tail and splenectomy, associating Whipple operation, Borrman typing, the art, lymph node dissection degree, residual stomach excise, prothrombin time;
18 variablees that (3) will filter out are done the polynary non-conditional logic regression analysis of two-value, carry out model testing, discriminant analysis, calculate the partial regression coefficient and the relative risk of each factor: OR=Exp (B), it is as follows to draw 8 factors that really influence the postoperative gastric cancer severe complication: blood loss, tumor TNM are by stages in associating body of pancreas tail and splenectomy, lymph node dissection degree, liver function Child-Pugh integration, the preceding chronic comorbidities of art, total gastrectomy, No16a group lymph node dissection, the art;
(4) a situation arises and prediction probability for every patient's of statistics post-operative complication reality, with the prediction probability is test variable, a situation arises with post-operative complication reality is state variable, do the analysis of experimenter's performance curve, estimate the value of this Forecasting Methodology according to area under curve, determine the optimum prediction cut off value according to outstanding mounting index, and estimate sensitivity, the specificity of this Forecasting Methodology;
(5) according to the logistic regression analysis result of above-mentioned steps 3, set up the forecast model of serious complication risk degree after gastric cancer operation: P=Exp ∑ B0+B1X1+ ... + BkXk/1+Exp ∑ B0+B1X1+ ... + BkXk, wherein P is a dependent variable, represent the risk probability value, X is an independent variable, represents each risk factor, and B is a partial regression coefficient, in conjunction with the best cut off value of determining by outstanding mounting index, promptly can be used for predicting the risk probability of every routine Patients with Gastric Cancer generation severe postoperative complication.
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