Kiemeney Lambertus A L M, Mochtar Chaidir A, Straatman Huub
Department of Urology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.
Urology. 2006 May;67(5):984-9. doi: 10.1016/j.urology.2005.11.049. Epub 2006 Apr 25.
Frequently, statistically significant prognostic factors are reported in published studies with suggestions that disease management should be modified. However, the clinical relevance of such factors is rarely quantified. We evaluated the accuracy of predicting the need for invasive treatment among patients with benign prostatic hyperplasia treated conservatively with alpha1-blockers.
Information on eight prognostic factors was collected from 280 patients treated with alpha1-blockers. Using the proportional hazards regression coefficients, a risk score for retreatment was calculated for each patient. The analyses were repeated on 1000 groups of 280 patients sampled from the original case series. The results from these "bootstrap analyses" were compared with the original results.
Three statistically significant predictors of retreatment were identified. The 20% of patients with the greatest risk score had an 18-month risk of retreatment of only 20% (this should ideally approach 100%). Analyses of less than one half of all the bootstrap samples resulted in the same three significant prognostic factors. The 20% of patients with the greatest risk score in each of the 1000 samples experienced a highly variable risk of retreatment of 0% to 42%.
Strongly significant predictors for retreatment suggest the need for a change in disease management, but 4 of the 5 high-risk patients would be overtreated with a modified policy. The subclassification of patients with a relatively low risk and high risk of retreatment appeared far from accurate. Internal validation procedures may warn against the invalid translation of statistical significance into clinical relevance.
在已发表的研究中,经常会报道具有统计学意义的预后因素,并建议改变疾病管理方式。然而,这些因素的临床相关性很少被量化。我们评估了对接受α1受体阻滞剂保守治疗的良性前列腺增生患者进行侵入性治疗需求预测的准确性。
从280例接受α1受体阻滞剂治疗的患者中收集了8个预后因素的信息。利用比例风险回归系数,为每位患者计算再治疗的风险评分。对从原始病例系列中抽取的1000组每组280例患者重复进行分析。将这些“自助法分析”的结果与原始结果进行比较。
确定了3个具有统计学意义的再治疗预测因素。风险评分最高的20%患者18个月时的再治疗风险仅为20%(理想情况下应接近100%)。对不到一半的自助法样本进行分析得到了相同的3个显著预后因素。在1000个样本中,每个样本中风险评分最高的20%患者的再治疗风险变化很大,为0%至42%。
再治疗的强显著预测因素表明需要改变疾病管理方式,但5例高风险患者中有4例会因改变后的策略而接受过度治疗。再治疗风险相对较低和较高的患者亚分类似乎远不准确。内部验证程序可能会警示不要将统计学意义无效地转化为临床相关性。