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Using heat maps to assess the multidimensional association of comorbidities with survival in older cancer patients treated with chemotherapy

机译:使用热图评估较老癌症患者的患者中患者的群体复合性与化疗治疗的多维协会

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? 2017 Elsevier Inc. ? 2017 Elsevier Inc. Objective To date, most comorbidity studies have analyzed either a subgroup of frequent diseases, or used summary instruments such as the Charlson score or the Cumulative Illness Rating Scale-Geriatric (CIRS-G). Yet, comorbidity is a multidimensional construct and impacts function, treatment tolerance, and survival. We assessed how heat maps can unveil specific patterns of comorbidities associated with overall survival (OS) in older cancer patients treated with chemotherapy. Material and Methods We reviewed four trials that prospectively evaluated comorbidities using CIRS-G. Eligible patients were 65 years or older and had solid tumors with 30 or more patients per tumor site. Heat maps were constructed based on CIRS-G scores and correlated with OS. Results Among 818 patients accrued, 399 were eligible: Median follow-up was 53.4 months and median OS was 19.6 months (95% CI: 16.5–24.2). In the univariate model for OS, patients with a severe CIRS-G score in 6 organ categories (3–4 in heart, hematopoietic, respiratory, and musculoskeletal-integument and 2–4 in upper GI and liver) had statistically worse OS than those with lower scores. According to a total risk score (TRS) based on hazard ratios for OS, OS of the low risk group (N = 309, TRS 2) was significantly higher (24.3 m vs. 10.8 m, HR = 2.05, 95% CI: 1.58–2.66). TRS was a predictor for OS independently from stage, primary site, prior chemotherapy, ECOG performance status, and IADL (HR = 1.94, 95% CI: 1.47–2.57). Conclusions High TRS was a predictor of poor survival. Comorbidity heat maps appear promising to identify diseases most affecting the OS of older cancer patients. Objective To date, most comorbidity studies have analyzed either a subgroup of frequent diseases, or used summary instruments such as the Charlson score or the Cumulative Illness Rating Scale-Geriatric (CIRS-G). Yet, comorbidity is a multidimensional construct and impacts function, treatment tolerance, and survival. We assessed how heat maps can unveil specific patterns of comorbidities associated with overall survival (OS) in older cancer patients treated with chemotherapy. Material and Methods We reviewed four trials that prospectively evaluated comorbidities using CIRS-G. Eligible patients were 65 years or older and had solid tumors with 30 or more patients per tumor site. Heat maps were constructed based on CIRS-G scores and correlated with OS. Results Among 818 patients accrued, 399 were eligible: Median follow-up was 53.4 months and median OS was 19.6 months (95% CI: 16.5–24.2). In the univariate model for OS, patients with a severe CIRS-G score in 6 organ categories (3–4 in heart, hematopoietic, respiratory, and musculoskeletal-integument and 2–4 in upper GI and liver) had statistically worse OS than those with lower scores. According to a total risk score (TRS) based on hazard ratios for OS, OS of the low risk group (N = 309, TRS < 2) was significantly higher (24.3 m vs. 10.8 m, HR = 2.05, 95% CI: 1.58–2.66). TRS was a predictor for OS independently from stage, primary site, prior chemotherapy, ECOG performance status, and IADL (HR = 1.94, 95% CI: 1.47–2.57). Conclusions High TRS was a predictor of poor survival. Comorbidity heat maps appear promising to identify diseases most affecting the OS of older cancer patients.
机译:还2017年elsevier公司? 2017年elsevier Inc.目的待迄今为止,大多数合并症研究分析了频繁疾病的亚组,或使用诸如Charlson得分或累积疾病评级规模 - 老年(CIRS-G)的摘要仪器。然而,合并率是多维构建体和影响功能,治疗耐受性和生存。我们评估了热图如何揭开与化疗治疗的较老癌症患者的整体存活(OS)相关的合并症的特定模式。材料和方法我们审查了四项试验,用于使用CIRS-G进行前瞻性评估的合并症。符合条件的患者65岁或以上,并且每肿瘤部位患者具有30例或更多患者。基于CIRS-G分数构建热图并与OS相关。结果818名患者累计,399名符合条件:中位随访时间为53.4个月,中位数OS是19.6个月(95%CI:16.5-24.2)。在单变量模型的操作系统中,6个器官类别中严重的CIRS-G分数(心脏病,造血,呼吸道和肌肉骨骼 - 整数和上部GI和肝脏中的2-4个)的患者具有统计学差的操作系统分数较低。根据基于OS的危险比的总风险评分(TRS),低风险组(n = 309,TR <2)的OS显着高出(24.3米,10.8米,HR = 2.05,95%CI :1.58-2.66)。 TRS是OS的预测因子,独立于阶段,主要部位,先前化疗,ECOG性能状态和IADL(HR = 1.94,95%CI:1.47-2.57)。结论高TRS是存活率差的预测因子。合并热图似乎有希望识别最癌症患者的疾病。目的迄今为止,大多数合并症研究已经分析了频繁疾病的亚组,或使用诸如Charlson评分或累积疾病评级规模 - 老年(CIRS-G)的摘要仪器。然而,合并率是多维构建体和影响功能,治疗耐受性和生存。我们评估了热图如何揭开与化疗治疗的较老癌症患者的整体存活(OS)相关的合并症的特定模式。材料和方法我们审查了四项试验,用于使用CIRS-G进行前瞻性评估的合并症。符合条件的患者65岁或以上,并且每肿瘤部位患者具有30例或更多患者。基于CIRS-G分数构建热图并与OS相关。结果818名患者累计,399名符合条件:中位随访时间为53.4个月,中位数OS是19.6个月(95%CI:16.5-24.2)。在单变量模型的操作系统中,6个器官类别中严重的CIRS-G分数(心脏病,造血,呼吸道和肌肉骨骼 - 整数和上部GI和肝脏中的2-4个)的患者具有统计学差的操作系统分数较低。根据基于OS的危险比的总风险评分(TRS),低风险组(n = 309,TRS <2)的OS显着高(24.3米,10.8米,HR = 2.05,95%CI: 1.58-2.66)。 TRS是OS的预测因子,独立于阶段,主要部位,先前化疗,ECOG性能状态和IADL(HR = 1.94,95%CI:1.47-2.57)。结论高TRS是存活率差的预测因子。合并热图似乎有希望识别最癌症患者的疾病。

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