P. Ross, C. Gerigk, M. Gonen, O. Yossepowitch, I. Cagiannos, P. Sogani, P. Scardino, M. Kattan
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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.","PeriodicalId":79436,"journal":{"name":"Seminars in urologic oncology","volume":"20 2 1","pages":"82-8"},"PeriodicalIF":0.0000,"publicationDate":"2002-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"235","resultStr":"{\"title\":\"Comparisons of nomograms and urologists' predictions in prostate cancer.\",\"authors\":\"P. Ross, C. Gerigk, M. Gonen, O. Yossepowitch, I. Cagiannos, P. Sogani, P. Scardino, M. 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引用次数: 235
摘要
当将nomograph应用于临床设置时,了解他们的预测与临床医生的预测相比较是至关重要的。比较存在于前列腺癌文献之外。我们回顾了这些比较,并进行了2个实验,比较临床医生对前列腺癌x线图的预测。通过Medline,我们检索了从1966年1月到1999年7月之间比较人类预测和nomogram预测的研究。接下来,我们进行了2项实验:(1)向17名泌尿科医生提供10例病例图,并要求他们预测每位患者5年无复发概率;(2)将63例前列腺癌患者的病例报告(包括完整的临床病史、完整的诊断资料和手术结果)提交给一组25名临床医生,要求他们预测器官局限性疾病。我们发现22项已发表的研究将人类专家与nomogram进行比较,超过一半(22项中的13项)显示nomogram的表现高于人类专家的水平。我们的第一个实验显示,泌尿科医生修改了165个nomogram预测,导致预测准确性下降(c-index从。67年。55, p < 0.05)。在我们的第二个实验中,临床医生对器官局限性疾病的预测与nomogram(受者工作特征曲线下面积[AUC]分别为0.78和0.79)相当。混合模型表明nomogram并没有提高临床医生的预测准确度(医生超额误差1.4%,P =。75、95%置信区间[CI]: -10.9% ~ 8.2%)。我们的数据表明,图似乎不会降低预测的准确性,它们可能在某些临床决策设置显著的好处。
Comparisons of nomograms and urologists' predictions in prostate cancer.
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.