问Cox模型的一致性值与mlr计算的c-指标不同。
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提问于 2018-11-29 15:46:18

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如果在mlr中使用带5倍交叉验证的重采样来训练cox模型，则通过打印每个折叠的Cox模型摘要输出的一致性值与由mlr计算的cindex值不同。我解释得不对吗？还是我用了太多的预测器？如果是的话，为何会出现这种差异呢？

在下面的示例中，mlr返回第一个折叠的cindex值为0.5093809，但cox摘要输出报告的一致性为0.76。我的数据可以在这里下载：data.csv?dl=0

重采样：

library(survival)
library(mlr)

mydata <- read.csv(file="test_data.csv", header=TRUE, sep=",",row.names=NULL)    
surv.task <- makeSurvTask(data = mydata, target = c("timeToEvent", "status"))
rdesc <- makeResampleDesc(method="CV", iters=5, stratify=TRUE)
r = resample("surv.coxph", surv.task, rdesc, models=TRUE)
r

Resample Result
Task: mydata
Learner: surv.coxph
Aggr perf: cindex.test.mean=0.5999838
Runtime: 0.151174

r$measures.test
 iter    cindex
1    1 0.5093809
2    2 0.7324649
3    3 0.4984653
4    4 0.6461876
5    5 0.6134201

请查看Cox模型第一页的摘要：

summary(getLearnerModel(r$models[[1]]))

Call:
survival::coxph(formula = f, data = data)

  n= 698, number of events= 65 

          coef  exp(coef)   se(coef)      z Pr(>|z|)    
V1  -0.1225832  0.8846323  0.1833418 -0.669 0.503748    
V2  -1.9815012  0.1378621  2.9565667 -0.670 0.502728    
V3  -0.5894775  0.5546170  1.9276623 -0.306 0.759758    
V4   0.5005582  1.6496418  0.9433060  0.531 0.595667    
V5   0.0179647  1.0181271  1.9273040  0.009 0.992563    
V6   0.7309210  2.0769926  1.9361340  0.378 0.705790    
V7  -0.0012070  0.9987937  0.0890533 -0.014 0.989186    
V8   0.1029020  1.1083828  0.0356533  2.886 0.003899 ** 
V9  -0.2728561  0.7612023  0.2311420 -1.180 0.237813    
V10 -0.0213663  0.9788604  0.0133210 -1.604 0.108725    
V11  0.2416705  1.2733746  0.2113099  1.144 0.252757    
V12 -0.0021392  0.9978631  0.0550684 -0.039 0.969014    
V13 -0.0047373  0.9952739  0.0073776 -0.642 0.520794    
V14  0.0119084  1.0119796  0.0036098  3.299 0.000971 ***
V15 -6.6529859  0.0012902  2.8566451 -2.329 0.019862 *  
V16 -0.0005712  0.9994290  0.0015808 -0.361 0.717842    
V17 -0.0058360  0.9941810  0.0970749 -0.060 0.952062    
V18 -0.0095129  0.9905322  0.0072980 -1.304 0.192402    
V19  0.0004149  1.0004150  0.0002001  2.074 0.038107 *  
V20  0.0001584  1.0001584  0.0002319  0.683 0.494487    
V21 -0.0010930  0.9989076  0.0045039 -0.243 0.808255    
V22 -0.0015312  0.9984700  0.0023389 -0.655 0.512699    
V23 -0.0441918  0.9567705  0.0936314 -0.472 0.636944    
V24  0.0475120  1.0486588  0.0681332  0.697 0.485590    
V25  0.1637753  1.1779496  0.1177553  1.391 0.164283    
V26 -0.0296841  0.9707521  0.0460953 -0.644 0.519593    
V27 -0.1181631  0.8885511  0.0824113 -1.434 0.151623    
V28  0.0081237  1.0081568  0.0106226  0.765 0.444419    
V29 -0.0409860  0.9598425  0.0282858 -1.449 0.147339    
V30  0.0006100  1.0006102  0.0002408  2.533 0.011293 *  
V31 -0.0016426  0.9983587  0.0054629 -0.301 0.763655    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

    exp(coef) exp(-coef) lower .95 upper .95
V1    0.88463     1.1304 6.176e-01    1.2671
V2    0.13786     7.2536 4.196e-04   45.2980
V3    0.55462     1.8030 1.268e-02   24.2562
V4    1.64964     0.6062 2.597e-01   10.4793
V5    1.01813     0.9822 2.330e-02   44.4965
V6    2.07699     0.4815 4.671e-02   92.3581
V7    0.99879     1.0012 8.388e-01    1.1893
V8    1.10838     0.9022 1.034e+00    1.1886
V9    0.76120     1.3137 4.839e-01    1.1974
V10   0.97886     1.0216 9.536e-01    1.0048
V11   1.27337     0.7853 8.416e-01    1.9267
V12   0.99786     1.0021 8.958e-01    1.1116
V13   0.99527     1.0047 9.810e-01    1.0098
V14   1.01198     0.9882 1.005e+00    1.0192
V15   0.00129   775.0952 4.776e-06    0.3485
V16   0.99943     1.0006 9.963e-01    1.0025
V17   0.99418     1.0059 8.219e-01    1.2025
V18   0.99053     1.0096 9.765e-01    1.0048
V19   1.00041     0.9996 1.000e+00    1.0008
V20   1.00016     0.9998 9.997e-01    1.0006
V21   0.99891     1.0011 9.901e-01    1.0078
V22   0.99847     1.0015 9.939e-01    1.0031
V23   0.95677     1.0452 7.964e-01    1.1495
V24   1.04866     0.9536 9.176e-01    1.1985
V25   1.17795     0.8489 9.352e-01    1.4837
V26   0.97075     1.0301 8.869e-01    1.0625
V27   0.88855     1.1254 7.560e-01    1.0443
V28   1.00816     0.9919 9.874e-01    1.0294
V29   0.95984     1.0418 9.081e-01    1.0146
V30   1.00061     0.9994 1.000e+00    1.0011
V31   0.99836     1.0016 9.877e-01    1.0091

Concordance= 0.76  (se = 0.037 )
Rsquare= 0.087   (max possible= 0.68 )
Likelihood ratio test= 63.69  on 31 df,   p=5e-04
Wald test            = 67.74  on 31 df,   p=2e-04
Score (logrank) test = 70.07  on 31 df,   p=7e-05