Kallogjeri Dorina, Piccirillo Jay F, Spitznagel Edward L, Steyerberg Ewout W
Clinical Outcomes Research Office, Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, Missouri, USA.
J Geriatr Oncol. 2012 Jul 1;3(3):238-245. doi: 10.1016/j.jgo.2012.01.006.
To examine the prognostic value of different comorbidity coding schemes for predicting survival of newly diagnosed elderly cancer patients. MATERIALS AND METHODS: We analyzed data from 8,867 patients aged 65 years of age or older, newly diagnosed with cancer. Comorbidities present at the time of diagnosis were collected using the Adult Comorbidity Evaluation-27 index (ACE-27). We examined multiple scoring schemes based on the individual comorbidity ailments, and their severity rating. Harrell's c index and Akaike Information Criterion (AIC) were used to evaluate the performance of the different comorbidity models. RESULTS: Comorbidity led to an increase in c index from 0.771 for the base model to 0.782 for a model that included indicator variables for every ailment. The prognostic value was however much higher for prostate and breast cancer patients. A simple model which considered linear scores from 0 to 3 per ailment, controlling for cancer type, was optimal according to AIC. CONCLUSION: The presence of comorbidity impacts on the survival of elderly cancer patients, especially for less lethal cancers, such as prostate and breast cancers. Different ailments have different impacts on survival, necessitating the use of different weights per ailment in a simple summary score of the ACE-27.
探讨不同合并症编码方案对预测新诊断老年癌症患者生存率的预后价值。材料与方法：我们分析了8867例年龄在65岁及以上新诊断为癌症患者的数据。使用成人合并症评估-27指数（ACE-27）收集诊断时存在的合并症。我们基于个体合并症疾病及其严重程度评分研究了多种评分方案。使用Harrell's c指数和赤池信息准则（AIC）来评估不同合并症模型的性能。结果：合并症导致c指数从基础模型的0.771增加到包含每种疾病指示变量的模型的0.782。然而，对于前列腺癌和乳腺癌患者，预后价值要高得多。根据AIC，一个简单的模型是最优的，该模型考虑了每种疾病从0到3的线性评分，并控制癌症类型。结论：合并症的存在影响老年癌症患者的生存，尤其是对于前列腺癌和乳腺癌等致死率较低的癌症。不同的疾病对生存有不同的影响，因此在ACE-27的简单汇总评分中，每种疾病需要使用不同的权重。
