印度新冠病毒病患者按人口统计学因素进行的生存分析：定量研究
Survival Analysis of Patients With COVID-19 in India by Demographic Factors: Quantitative Study.
作者信息
Kundu Sampurna, Chauhan Kirti, Mandal Debarghya
机构信息
Department of Mathematical Demography and Statistics, International Institute for Population Sciences, Mumbai, India.
出版信息
JMIR Form Res. 2021 May 6;5(5):e23251. doi: 10.2196/23251.
BACKGROUND
Studies of the transmission dynamics of COVID-19 have depicted the rate, patterns, and predictions of cases of this pandemic disease. To combat transmission of the disease in India, the government declared a lockdown on March 25, 2020. Even after this strict lockdown was enacted nationwide, the number of COVID-19 cases increased and surpassed 450,000. A positive point to note is that the number of recovered cases began to slowly exceed that of active cases. The survival of patients, taking death as the event that varies by age group and sex, is noteworthy.
OBJECTIVE
The aim of this study was to conduct a survival analysis to establish the variability in survivorship of patients with COVID-19 in India by age group and sex at different levels, that is, the national, state, and district levels.
METHODS
The study period was taken from the date of the first reported case of COVID-19 in India, which was January 30, 2020, up to June 30, 2020. Due to the amount of underreported data and removal of missing columns, a total sample of 26,815 patients was considered. Kaplan-Meier survival estimation, the Cox proportional hazard model, and the multilevel survival model were used to perform the survival analysis.
RESULTS
The Kaplan-Meier survival function showed that the probability of survival of patients with COVID-19 declined during the study period of 5 months, which was supplemented by the log rank test (P<.001) and Wilcoxon test (P<.001) to compare the survival functions. Significant variability was observed in the age groups, as evident from all the survival estimates; with increasing age, the risk of dying of COVID-19 increased. The Cox proportional hazard model reiterated that male patients with COVID-19 had a 1.14 times higher risk of dying than female patients (hazard ratio 1.14; SE 0.11; 95% CI 0.93-1.38). Western and Central India showed decreasing survival rates in the framed time period, while Eastern, North Eastern, and Southern India showed slightly better results in terms of survival.
CONCLUSIONS
This study depicts a grave scenario of decreasing survival rates in various regions of India and shows variability in these rates by age and sex. In essence, we can safely conclude that the critical appraisal of the survival rate and thorough analysis of patient data in this study equipped us to identify risk groups and perform comparative studies of various segments in India.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1101/2020.08.01.20162115.
背景
对2019冠状病毒病（COVID-19）传播动态的研究描绘了这种大流行疾病的病例发生率、模式及预测情况。为抗击该疾病在印度的传播，政府于2020年3月25日宣布实施封锁。即便在全国实施了这种严格的封锁措施之后，COVID-19病例数仍在增加，并超过了45万例。值得注意的一个积极方面是，康复病例数开始逐渐超过现症病例数。以死亡作为因年龄组和性别而异的事件，患者的生存情况值得关注。
目的
本研究的目的是进行生存分析，以确定印度COVID-19患者在国家、邦和地区不同层面按年龄组和性别划分的生存差异。
方法
研究时间段为印度首例COVID-19报告病例的日期（2020年1月30日）至2020年6月30日。由于存在数据漏报情况以及对缺失列的剔除，共纳入26815例患者作为样本。采用Kaplan-Meier生存估计法、Cox比例风险模型和多水平生存模型进行生存分析。
结果
Kaplan-Meier生存函数显示，在5个月的研究期间，COVID-19患者的生存概率下降，对数秩检验（P<0.001）和Wilcoxon检验（P<0.001）进一步佐证了对生存函数的比较。从所有生存估计结果来看，各年龄组存在显著差异；随着年龄增长，COVID-19死亡风险增加。Cox比例风险模型重申，COVID-19男性患者死亡风险比女性患者高1.14倍（风险比1.14；标准误0.11；95%置信区间0.93 - 1.38）。在设定时间段内，印度西部和中部地区生存率呈下降趋势，而东部、东北部和南部地区在生存方面表现略好。
结论
本研究描绘了印度各地区生存率下降的严峻情况，并显示了这些比率在年龄和性别上的差异。从本质上讲，我们可以有把握地得出结论，本研究中生存率的批判性评估以及对患者数据的深入分析使我们能够识别风险群体，并对印度不同群体进行比较研究。
国际注册报告识别码（IRRID）：RR2-10.1101/2020.08.01.20162115。
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