Seage G R, Gatsonis C, Weissman J S, Haas J S, Cleary P D, Fowler F J, Massagli M P, Stone V E, Craven D E, Makadon H, Goldberg J, Coltin K, Levin K S, Epstein A M
Institute for Urban Health Policy and Research, Boston Department of Health and Hospitals, Mass., USA.
Am J Public Health. 1997 Apr;87(4):567-73. doi: 10.2105/ajph.87.4.567.
This study developed a new acquired immunodeficiency syndrome (AIDS) severity system by including diagnostic, physiological, functional, and sociodemographic factors predictive of survival.
Three-hundred five persons with AIDS in Boston were interviewed; their medical records were reviewed and vital status ascertained.
Overall median (+/- SD) survival for the cohort from the first interview until death was 560 +/- 14.4 days. The best model for predicting survival, the Boston AIDS Survival Score, included the Justice score (stage 2 relative hazard [RH] = 1.25, 95% confidence interval [CI] = 0.80, 1.96; stage 3 RH = 1.76, 95% CI = 1.15, 2.70), a newly developed opportunistic disease score (Boston Opportunistic Disease Survival Score; stage 2 RH = 1.35, 95% CI = 0.90, 2.02; stage 3 RH = 2.10, 95% CI = 1.38, 3.18), and measures of activities of daily living (any intermediate limitations, RH = 1.84, 95% CI = 1.05, 3.21; any basic limitations, RH = 2.60, 95% CI = 1.44, 4.69). This model had substantially greater predictive power (R2 = .17, C statistic = .68) than the Justice score alone (R2 = .09, C statistic = .61).
Incorporating data on clinically important events and functional status into a physiologically based system can improve the prediction of survival with AIDS.
本研究通过纳入预测生存的诊断、生理、功能和社会人口学因素，开发了一种新的获得性免疫缺陷综合征（艾滋病）严重程度系统。
对波士顿的305名艾滋病患者进行了访谈；查阅了他们的病历并确定了生命状态。
该队列从首次访谈至死亡的总体中位（±标准差）生存期为560±14.4天。预测生存的最佳模型，即波士顿艾滋病生存评分，包括正义评分（2期相对风险[RH]=1.25，95%置信区间[CI]=0.80，1.96；3期RH=1.76，95%CI=1.15，2.70）、新开发的机会性疾病评分（波士顿机会性疾病生存评分；2期RH=1.35，95%CI=0.90，2.02；3期RH=2.10，95%CI=1.38，3.18）以及日常生活活动指标（任何中度受限，RH=1.84，95%CI=1.05，3.21；任何基本受限，RH=2.60，95%CI=1.44，4.69）。该模型的预测能力（R2=0.17，C统计量=0.68）比单独的正义评分（R2=0.09，C统计量=0.61）有显著提高。
将关于临床重要事件和功能状态的数据纳入基于生理的系统可以改善对艾滋病患者生存的预测。
