Division of Biostatistics, Kalinga Institute of Medical Sciences, Bhubaneswar, Odisha; Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India.
Department of Surgical Oncology, BRA Institute Rotary Cancer Hospital, All India Institute of Medical Sciences, New Delhi, India.
J Cancer Res Ther. 2021 Jul-Sep;17(4):982-987. doi: 10.4103/jcrt.JCRT_49_19.
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.
To identify the risk factors and predict LRR using competing risk hazard model and to compare them with those using conventional hazard model.
This was a retrospective study from a tertiary care cancer hospital in India.
Data of 2114 breast cancer patients undergoing surgery were used from patient's record files (1993-2014).
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.
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.
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.
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。因为后者比 LRR 更致命。它可能改变正在进行的乳腺癌治疗，并可能改变 LRR 的机会。尽管一些早期研究评估了新辅助化疗（NACT）对 LRR 的影响，但它们没有为此使用竞争风险回归模型。
使用竞争风险风险模型确定 LRR 的危险因素和预测，并将其与传统风险模型进行比较。
这是印度一家三级癌症医院的回顾性研究。
使用来自患者病历档案的 2114 例乳腺癌患者数据（1993-2014 年）。
使用 Fine 和 Gray 竞争风险回归来对从手术到 LRR 的时间进行建模，考虑远处转移和死亡作为竞争事件。此外，还使用不考虑竞争风险的特定于原因的 Cox 回归来对从手术到 LRR 的时间进行建模。
十个以上阳性淋巴结（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]）和术后放疗（HR [95% CI]：0.52 [0.29-0.94]）与 LRR 显著相关。然而，忽略竞争风险的传统生存分析高估了累积发生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：如果存在竞争风险，则需要将其纳入生存分析中。发现 NACT 与 LRR 的风险增加相关，这可能是因为它主要用于预后不良的患者。
如果存在竞争风险，则需要将其纳入生存分析中。发现 NACT 与 LRR 的风险增加相关，这可能是因为它主要用于预后不良的患者。
