Context: While analyzing locoregional recurrences (LRRs), it is necessary to consider distant metastasis as a competing event. Because, later one is more fatal than LRR. It may change ongoing treatment of breast cancer and may alter the chance of LRR. Although some earlier studies assessed the effect of neoadjuvant chemotherapy (NACT) on LRR, they did not use competing risk regression model for it.
Aims: To identify the risk factors and predict LRR using competing risk hazard model and to compare them with those using conventional hazard model.
Settings and Design: This was a retrospective study from a tertiary care cancer hospital in India.
Subjects and Methods: Data of 2114 breast cancer patients undergoing surgery were used from patient's record files (1993–2014).
Statistical Analysis: Fine and Gray competing risk regression was used to model time from surgery to LRR, considering distant metastasis and death as the competing events. Further, cause-specific Cox regression was used to model time from surgery to LRR without considering competing risk.
Results: Greater than ten positive nodes (hazard ratio [HR] [95% confidence interval (CI)]: 2.19 [1.18–4.03]), skin involvement (HR [95% CI]: 2.75 [1.50–5.05]), NACT (HR [95% CI]: 1.90 [1.06–3.40]), invasive tumor in inner quadrant (HR [95% CI]: 1.78 [0.98–3.24]), and postoperative radiotherapy (HR [95% CI]: 0.52 [0.29–0.94]) were found to be significantly associated with LRR. However, conventional survival analysis ignoring competing risk overestimated cumulative incidence function and underestimated survival. Competing risk regression provided relatively more precise CI.
Conclusions: Competing risks, if any, need to be incorporated in the survival analysis. NACT was found to be associated with higher risk for LRR, which may be because of administering it mainly to patients with bad prognosis.
Conclusions: Competing risks, if any, need to be incorporated in the survival analysis. NACT was found to be associated with higher risk for LRR, which may be because of administering it mainly to patients with bad prognosis.


中文翻译：

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比较考虑和不考虑竞争风险的风险模型，以评估新辅助化疗对乳腺癌患者局部复发的影响


背景：在分析局部区域复发 (LRR) 时，有必要将远处转移视为竞争事件。因为，后一个比 LRR 更致命。它可能会改变正在进行的乳腺癌治疗，并可能改变 LRR 的机会。尽管一些早期的研究评估了新辅助化疗 (NACT) 对 LRR 的影响，但他们没有使用竞争风险回归模型。
目的：识别风险因素并使用竞争风险风险模型预测 LRR，并将其与使用传统风险模型的风险因素进行比较。
设置和设计：这是来自印度一家三级癌症医院的回顾性研究。
主题和方法：2114 名接受手术的乳腺癌患者的数据来自患者的记录文件（1993-2014 年）。
统计分析：精细和灰色竞争风险回归用于模拟从手术到 LRR 的时间，将远处转移和死亡视为竞争事件。此外，特定原因的 Cox 回归用于模拟从手术到 LRR 的时间，而不考虑竞争风险。
结果：大于 10 个阳性淋巴结（风险比 [HR] [95% 置信区间 (CI)]：2.19 [1.18–4.03]），皮肤受累（HR [95% CI]：2.75 [1.50–5.05]），NACT（HR [95% CI]：1.90 [1.06–3.40]），内象限浸润性肿瘤（HR [95% CI]：1.78 [0.98–3.24]），术后放疗（HR [95% CI]：0.52 [0.29– 0.94]）被发现与 LRR 显着相关。然而，忽略竞争风险的传统生存分析高估了累积发病率函数并低估了生存率。竞争风险回归提供了相对更精确的 CI。
结论：竞争风险，如果有的话，需要纳入生存分析。NACT 被发现与更高的 LRR 风险相关，这可能是因为它主要用于预后不良的患者。
结论：竞争风险（如果有）需要纳入生存分析。NACT 被发现与更高的 LRR 风险相关，这可能是因为它主要用于预后不良的患者。