Catto James W F, Abbod Maysam F, Linkens Derek A, Larré Stéphane, Rosario Derek J, Hamdy Freddie C
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK.
Clin Cancer Res. 2009 May 1;15(9):3150-5. doi: 10.1158/1078-0432.CCR-08-1960. Epub 2009 Mar 31.
Bladder cancer recurrence occurs in 40% of patients following radical cystectomy (RC) and pelvic lymphadenectomy (PLND). Although recurrence can be reduced with adjuvant chemotherapy, the toxicity and low response rates of this treatment restrict its use to patients at highest risk. We developed a neurofuzzy model (NFM) to predict disease recurrence following RC and PLND in patients who are not usually administered adjuvant chemotherapy.
The study comprised 1,034 patients treated with RC and PLND for bladder urothelial carcinoma. Four hundred twenty-five patients were excluded due to lymph node metastases and/or administration of chemotherapy. For the remaining 609 patients, we obtained complete clinicopathologic data relating to their tumor. We trained, tested, and validated two NFMs that predicted risk (Classifier) and timing (Predictor) of post-RC recurrence. We measured the accuracy of our model at various postoperative time points.
Cancer recurrence occurred in 172 (28%) patients. With a median follow-up of 72.7 months, our Classifier NFM identified recurrence with an accuracy of 0.84 (concordance index 0.92, sensitivity 0.81, and specificity 0.85) and an excellent calibration. This was better than two predictive nomograms (0.72 and 0.74 accuracies). The Predictor NFMs identified the timing of tumor recurrence with a median error of 8.15 months.
We have developed an accurate and well-calibrated model to identify disease recurrence following RC and PLND in patients with nonmetastatic bladder urothelial carcinoma. It seems superior to other available predictive methods and could be used to identify patients who would potentially benefit from adjuvant chemotherapy.
根治性膀胱切除术（RC）和盆腔淋巴结清扫术（PLND）后，40%的患者会出现膀胱癌复发。尽管辅助化疗可降低复发率，但该治疗的毒性和低反应率限制了其仅用于高危患者。我们开发了一种神经模糊模型（NFM），以预测通常不接受辅助化疗的患者在RC和PLND后的疾病复发情况。
本研究纳入了1034例接受RC和PLND治疗膀胱尿路上皮癌的患者。425例患者因淋巴结转移和/或接受化疗而被排除。对于其余609例患者，我们获取了与他们肿瘤相关的完整临床病理数据。我们训练、测试并验证了两个NFM，分别用于预测RC后复发的风险（分类器）和时间（预测器）。我们在术后不同时间点测量了模型的准确性。
172例（28%）患者出现癌症复发。中位随访72.7个月，我们的分类器NFM识别复发的准确率为0.84（一致性指数0.92，敏感性0.81，特异性0.85），校准良好。这优于两个预测列线图（准确率分别为0.72和0.74）。预测器NFM识别肿瘤复发时间的中位误差为8.15个月。
我们开发了一种准确且校准良好的模型，用于识别非转移性膀胱尿路上皮癌患者在RC和PLND后的疾病复发情况。它似乎优于其他可用的预测方法，可用于识别可能从辅助化疗中获益的患者。
