Ross Phillip L, Gerigk Claudia, Gonen Mithat, Yossepowitch Ofer, Cagiannos Ilias, Sogani Pramod C, Scardino Peter T, Kattan Michael W
Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.
Semin Urol Oncol. 2002 May;20(2):82-8. doi: 10.1053/suro.2002.32490.
When applying nomograms to a clinical setting it is essential to know how their predictions compare with clinicians'. Comparisons exist outside of the prostate cancer literature. We reviewed these comparisons and conducted 2 experiments comparing predictions of clinicians with prostate cancer nomograms. By using Medline, we searched studies from January 1966 to July 1999 that compared human predictions with nomogram predictions. Next, we conducted 2 experiments: (1) 17 urologists were presented with 10 case vignettes and asked to predict the 5-year recurrence-free probabilities for each patient; (2) case presentations of 63 prostate cancer patients (including full clinical histories with complete diagnostic data and surgical findings) were made to a group of 25 clinicians who were asked to predict organ-confined disease. We found 22 published studies comparing human experts with nomograms, greater than half (13 of 22) showed the nomogram performing above the level of the human expert. Our first experiment showed urologist modification of 165 nomogram predictions led to a decrease in prediction accuracy (c-index decreased from.67 to.55, P <.05). In our second experiment, clinician predictions of organ-confined disease were comparable to the nomogram (area under the receiver operating characteristic curve [AUC] 0.78 and 0.79, respectively). A mixed-model suggests the nomogram did not augment clinician prediction accuracy (doctor excess error 1.4%, P =.75, 95% confidence interval [CI]: -10.9% to 8.2%). Our data suggest that nomograms do not seem to diminish predictive accuracy and they may be of significant benefit in certain clinical decision making settings.
在临床环境中应用列线图时，了解其预测结果与临床医生的预测结果相比如何至关重要。前列腺癌文献之外也存在相关比较。我们回顾了这些比较，并进行了两项实验，将临床医生的预测与前列腺癌列线图的预测进行比较。通过使用医学在线数据库（Medline），我们检索了1966年1月至1999年7月间比较人类预测与列线图预测的研究。接下来，我们进行了两项实验：（1）向17名泌尿科医生展示10个病例 vignettes，并要求他们预测每位患者的5年无复发生存概率；（2）向一组25名临床医生展示63例前列腺癌患者的病例介绍（包括完整的临床病史、完整的诊断数据和手术结果），并要求他们预测器官局限性疾病。我们发现有22项已发表的研究比较了人类专家与列线图，超过一半（22项中的13项）显示列线图的表现高于人类专家水平。我们的第一项实验表明，泌尿科医生对165个列线图预测进行调整后，预测准确性下降（c指数从0.67降至0.55，P < 0.05）。在我们的第二项实验中，临床医生对器官局限性疾病的预测与列线图相当（受试者操作特征曲线下面积[AUC]分别为0.78和0.79）。混合模型表明列线图并未提高临床医生的预测准确性（医生额外误差为1.4%，P = 0.75，95%置信区间[CI]：-10.9%至8.2%）。我们的数据表明，列线图似乎不会降低预测准确性，并且它们在某些临床决策环境中可能具有显著益处。
