All classifiers were able to yield a predictive model for the OPC data set.The CART method gave the best statistical power for a MIC 4 mg/liter for detecting failures,although the rest of classifiers also exhibited high statistical power (Ta- ble 1).However,for candidemia the scenario was completely different.CART and Naïve Bayes methods were able to dis- cover a MIC value that split the populations,but the statistical power was limited (although it was slightly better for CART).Regarding dose/MIC targets,results were similar for the OPC data set.All classifiers were able to determine a dose/ MIC value that split the populations of successes and failures,with areas under the ROC curves above 0.85.However,for candidemia,only CART produced the same dose/MIC value as that determined for the OPC data set,but the CART determination had little statistical power (Table 2).
所有的分类都能够产生一个预测模型的OPC数据集.尽管其他分类法的统计功效也相当高,但其中Cart的方法在MIC > 4mg /liter的情况下的失败预测具有最佳统计功效(表1).然而对于念珠菌的情况完全不同.CART和朴素贝叶斯方法能够找到良好MIC值来分划人群,但统计功效却很有限(其中CART略强一些).对于dose/MIC的目标值,结果与OPC人群实验数据集结果相似.所有分类法都能够确定可以以成功与失败来分划人群的dose/ MIC,其相应的ROC曲线面积为0.85.然而对于念珠菌,只有CART生成了相同的dose/MIC决定值,但具有很低的统计功效.
The determinations for the two cohorts had different values with respect to statistical power,and this merits an explana- tion.For the OPC cohort,85 cases had a MIC 4 mg/liter,but there were only 4 cases for candidemia that showed this value.The lack of strains with MIC 4 mg/liter in the candidemia cohort explains the limited statistical power of the models.However,the models for the OPC and candidemia datasets gave the same values for MIC and for dose/MIC for at least one classifier.Therefore,the results obtained for the whole data set can be considered if the models produce the same MIC or dose/MIC when the datasets are analyzed separately,despite candidemia and OPC representing quite different clin- ical situations.If several models satisfy this circumstance,the statistical power of the analyses must be taken into account.
值得解释的是,两个病例群体的区间分划具有不同的预测值和统计功效.对于患有OPC的病例,85例的MIC > 4 mg/liter,但念珠菌患者中这样的病例只有4例.念珠菌患者中MIC > 4 mg/liter 群体的缺乏解释了统计功效的局限性.
然而,OPC和念珠菌患者群体数据模型得出的MIC以及dose/MIC的值在至少一种分类法下的结果是相同的.因此,若分别研究的数据却产生了相同的MIC或dose/MIC值,那么急事OPC与念珠菌血病代表着截然不同的临床情况,但是所有总体仍然可以合并考虑.在整个数据集得到的结果可以认为如果模型产生同样的MIC或剂量/麦克风时,数据集分别进行了分析,尽管念珠菌,代表完全不同的临床情况下的OPC.如果几个模型都满足同一情形,则此时必须考虑分析的统计功效.
The CART model produced identical target values for the two datasets and the highest statistical power in satisfying both sets of circumstances.The CART model gave a MIC 4 mg/liter as the breakpoint of resistance,with a sensitivity of 87%,a false-positive rate of 8%,an area under the ROC curve of 0.89,and an MCC index of 0.80 (Table 1).In addition,a dose/MIC 75 is proposed as the target to achieve treatment success.This means that a fluconazole dose of 400 mg/day will cover all strains with a fluconazole MIC of 4 mg/liter or less.The sensitivity of this target is 91%,with a false-positive rate of 10%,an area under the ROC curve of 0.90,and an MCC index of 0.80 (Table 2).
CART模型下两个数据集产生的目标值相同,且在两种情形下的统计功效均为最高.CART模型给出的抗感临界点MIC > 4 mg/liter,此时敏感度87%,假阳性率为8%,ROC曲线下面积0.89,MCC系数为0.80(表1).此外,评判成功治疗的目标指标一般认定为dose/MIC > 75.这意味着400 mg/天的氟康唑剂量将覆盖MIC值为4mg/liter及以下的所有菌株.这一目标的敏感度为91%,假阳性率10%,ROC曲线下面积为0.90,MCC指数为0.80 (表2).