Development and validation of a prognostic model incorporating patient reported outcomes for advanced gastric and esophageal carcinoma (AGOC) using individual patient data from two AGITG randomized clinical trials.

IF 5.1 1区 医学 Q1 GASTROENTEROLOGY & HEPATOLOGY
Sayeda Kamrun Naher, David Espinoza, Peter Grimison, Kohei Shitara, Nick Pavlakis, David Goldstein, Martin R Stockler, Rebecca Mercieca-Bebber, Katrin Marie Sjoquist
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引用次数: 0

Abstract

Background: We developed and validated a prognostic model incorporating readily accessible clinicopathological data and specific patient-reported outcomes (PROs).

Methods: We used data from two randomized trials comparing regorafenib to placebo: AGITG INTEGRATE IIa (n = 251) for model development and AGITG INTEGRATE (n = 152) for validation. Candidate variables were chosen from a systematic literature review and expert consultation. Significant prognostic factors in the multivariable model were identified using univariable Cox proportional hazards models with a p-value of < 0.1. Multivariable Cox proportional hazards models were developed using clinicopathological and PRO variables, with model selection refined using least absolute shrinkage and selection operator (LASSO). The model's discrimination and calibration were assessed using concordance indices (C-statistics) and calibration plots.

Results: Univariable analysis identified 9 clinicopathological variables and 4 PRO domains that were prognostic for overall survival: body mass index (BMI), ECOG performance status, number of metastatic sites, liver involvement, treatment with regorafenib, neutrophil-lymphocyte ratio (NLR), LDH, albumin, CA 19-9, appetite loss, constipation, fatigue, and pain. The initial multivariable model (M1) incorporated geographic region (Asia vs non-Asia), performance status, number of metastatic sites, treatment with regorafenib, NLR, BMI, LDH, CA 19-9, and albumin. The preferred multivariable model (M2), including the abovementioned variables plus the 4 PROs, demonstrated superior discriminative ability with higher C-statistic values than models without PROs. Plots supported the model's calibration.

Conclusions: Incorporating PROs into prognostic models for AGOC improved the accuracy of survival predictions. Further research is needed to validate its use in routine clinical practice.

利用两项AGITG随机临床试验的个体患者数据,开发和验证纳入晚期胃食管癌(AGOC)患者报告结果的预后模型。
背景:我们开发并验证了一个预后模型,该模型结合了易于获取的临床病理数据和特定的患者报告结果(PROs)。方法:我们使用两项比较瑞非尼与安慰剂的随机试验的数据:AGITG INTEGRATE IIa (n = 251)用于模型开发,AGITG INTEGRATE (n = 152)用于验证。候选变量是从系统的文献回顾和专家咨询中选择的。使用单变量Cox比例风险模型(p值为)确定多变量模型中的重要预后因素。结果:单变量分析确定了9个临床病理变量和4个PRO域,这些变量与总生存期有关。体重指数(BMI)、ECOG表现状态、转移部位数量、肝脏受累、瑞非尼治疗、中性粒细胞淋巴细胞比(NLR)、LDH、白蛋白、CA 19-9、食欲减退、便秘、疲劳和疼痛。最初的多变量模型(M1)包括地理区域(亚洲与非亚洲)、表现状态、转移部位数量、瑞非尼治疗、NLR、BMI、LDH、CA 19-9和白蛋白。优选多变量模型(M2)包括上述变量和4个PROs,其判别能力优于不含PROs的模型,c统计值更高。图支持模型的校准。结论:将PROs纳入AGOC的预后模型可提高生存预测的准确性。需要进一步的研究来验证其在常规临床实践中的应用。
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来源期刊
Gastric Cancer
Gastric Cancer 医学-胃肠肝病学
CiteScore
14.70
自引率
2.70%
发文量
80
审稿时长
6-12 weeks
期刊介绍: Gastric Cancer is an esteemed global forum that focuses on various aspects of gastric cancer research, treatment, and biology worldwide. The journal promotes a diverse range of content, including original articles, case reports, short communications, and technical notes. It also welcomes Letters to the Editor discussing published articles or sharing viewpoints on gastric cancer topics. Review articles are predominantly sought after by the Editor, ensuring comprehensive coverage of the field. With a dedicated and knowledgeable editorial team, the journal is committed to providing exceptional support and ensuring high levels of author satisfaction. In fact, over 90% of published authors have expressed their intent to publish again in our esteemed journal.
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