Table_1_Effects of Surgery on Survival of Early-Stage Patients With SCLC: Propensity Score Analysis and Nomogram Construction in SEER Database.DOCX (592.81 kB)

Table_1_Effects of Surgery on Survival of Early-Stage Patients With SCLC: Propensity Score Analysis and Nomogram Construction in SEER Database.DOCX

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posted on 24.04.2020 by Yuyan Wang, Qiwen Zheng, Bo Jia, Tongtong An, Jun Zhao, Meina Wu, Minglei Zhuo, Jianjie Li, Jia Zhong, Hanxiao Chen, Xue Yang, Yujia Chi, Zhi Dong, Boris Sepesi, Jianjun Zhang, Carl M. Gay, Ziping Wang

Purpose: We aimed to assess the survival benefit of surgery for patients with stage IA–IIB small cell lung cancer (SCLC) and construct a nomogram for predicting overall survival (OS).

Methods: Patients who had been diagnosed with stage IA–IIB SCLC between 2004 and 2014 and who had received active treatment were selected from the Surveillance, Epidemiology, and End Results database. The primary endpoint was OS. Cox proportional hazards models and propensity score (PS) analyses were used to compare the associations between surgery and OS. The probability of 1- and 3-year OS was predicted using a nomogram.

Results: We reviewed 2,246 patients. The median OS of the surgery and non-surgery groups was 35 months and 19 months, respectively. Multivariable Cox proportional hazards models showed a survival benefit in the surgery group (hazards ratio [HR], 0.642; 95% confidence interval [CI], 0.557–0.740; P < 0.001). To balance the between-group measurable confounders, the impact of surgery on OS was assessed using PS matching. After PS matching, OS analysis still favored surgical resection. The PS-stratification, PS-weighting, and PS-adjustment models showed similar results to demonstrate a statistically significant benefit for surgery. Further, the nomogram was well calibrated and had good discriminative ability (Harrell's C-index = 0.645).

Conclusion: Our analysis suggests that surgery is a viable option for patients with early-stage SCLC. Our nomogram is a viable tool for quantifying treatment trade-off assumptions and may assist clinicians in decision-making. Future work is needed to validate our results and improve our tools.

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