Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-dong 50, Gangnam-gu, Seoul 135-710, South Korea.
World J Gastroenterol. 2011 Dec 28;17(48):5310-6. doi: 10.3748/wjg.v17.i48.5310.
To evaluate the clinical parameters and identify a better method of predicting pathological complete response (pCR).
We enrolled 249 patients from a database of 544 consecutive rectal cancer patients who underwent surgical resection after preoperative chemoradiation therapy (PCRT). A retrospective review of morphological characteristics was then performed to collect data regarding rectal examination findings. A scoring model to predict pCR was then created. To validate the ability of the scoring model to predict complete regression.
Seventy patients (12.9%) achieved a pCR. A multivariate analysis found that pre-CRT movability (P = 0.024), post-CRT size (P = 0.018), post-CRT morphology (P = 0.023), and gross change (P = 0.009) were independent predictors of pCR. The accuracy of the scoring model was 76.8% for predicting pCR with the threshold set at 4.5. In the validation set, the accuracy was 86.7%.
Gross changes and morphological findings are important predictors of pathological response. Accordingly, PCRT response is best predicted by a combination of clinical, laboratory and metabolic information.
评估临床参数并确定预测病理完全缓解（pCR）的更好方法。
我们从 544 例连续接受术前放化疗（PCRT）后行手术切除的直肠癌患者数据库中纳入 249 例患者。然后回顾性分析形态特征，收集直肠检查结果数据。然后创建预测 pCR 的评分模型。为了验证评分模型预测完全消退的能力。
70 例（12.9%）患者达到 pCR。多变量分析发现，术前 CRT 可移动性（P=0.024）、术后 CRT 大小（P=0.018）、术后 CRT 形态（P=0.023）和大体变化（P=0.009）是 pCR 的独立预测因子。评分模型预测 pCR 的准确率为 76.8%，阈值设定为 4.5。在验证集中，准确率为 86.7%。
大体变化和形态学发现是病理反应的重要预测因子。因此，PCRT 反应最好通过临床、实验室和代谢信息的组合来预测。
