Quantitative Health Sciences, Lerner Research Institute (B.L., N.T.), Cleveland Clinic, Ohio.
Center for Outcomes Research & Evaluation, Neurological Institute (B.L., N.T., A.S., I.L.K.), Cleveland Clinic, Ohio.
Circ Cardiovasc Qual Outcomes. 2021 Nov;14(11):e007960. doi: 10.1161/CIRCOUTCOMES.121.007960. Epub 2021 Nov 2.
Caregivers, or proxies, often complete patient-reported outcomes (PROs) on behalf of patients; yet, research has demonstrated proxies rate patient outcomes worse than patients rate their own outcomes. To improve interpretability of PROs in group-level analyses, our study aimed to identify optimal approaches for reducing proxy-introduced bias in the analysis of PROs.
Data were simulated based on 200 patients with stroke and their proxies who both completed 9 PROMIS domains as part of a cross-sectional study. The sample size was varied as 50, 100, 200, and 500, and the proportion of patients with proxy-respondents was varied as 10%, 20%, and 50%. Six methods for handling proxy-completions were investigated: (1) complete case analysis; (2) proxy substitution; (3) Method 2 plus proxy adjustment; (4) Method 3 including inverse-probability of treatment weighting; (5) multiple imputation; (6) linear equating. These methods were evaluated by comparing average bias in PROMIS -scores (estimated versus observed patient-only responses), as well as by comparing estimated regression coefficients to models using patient-only responses.
Overall mean -score differences ranged from 0 to 1.75. The range of mean differences varied by the 6 methods with methods 1 and 5 providing estimates closest to the observed mean. In regression models, all but inverse-probability of treatment weighting resulted in low bias when proxy-completions were 10% to 20%. With 50% proxy-completions, method 5 resulted in less accurate estimations while methods 1 to 3 provided less proxy-introduced bias. Bias remained low across domain and varying sample sizes but increased with larger percentages of proxy-respondents.
Our study found modest proxy-introduced bias when estimating PRO scores or regression estimates across multiple domains of health. This bias remained low, even when sample size was 50 and there were large proportions of proxy-completions. While many of these methods can be chosen for including proxies in stroke PRO research with <20% proxy-respondents, proxy substitution with adjustment resulted in low bias with 50% proxy-respondents.
护理人员或代理人经常代表患者完成患者报告的结果（PROs）；然而，研究表明代理人对患者结果的评分比患者自评的结果差。为了提高 PROs 在组水平分析中的可解释性，我们的研究旨在确定减少分析中代理引入偏差的最佳方法。
基于 200 名中风患者及其代理人的横断面研究数据，这些患者和代理人均完成了 9 个 PROMIS 领域。样本量分别为 50、100、200 和 500，代理应答者的比例分别为 10%、20%和 50%。调查了六种处理代理完成情况的方法：（1）完全案例分析；（2）代理替代；（3）方法 2 加代理调整；（4）包括逆处理权重的方法 3；（5）多重插补；（6）线性等效。通过比较 PROMIS 评分的平均偏差（估计值与仅患者的观察反应），以及通过比较仅患者反应的模型中估计的回归系数，来评估这些方法。
总体平均得分差异在 0 到 1.75 之间。6 种方法的平均差异范围不同，方法 1 和 5 提供的估计值最接近观察到的平均值。在回归模型中，当代理完成率为 10%至 20%时，除逆处理权重外，所有方法均导致低偏差。当代理完成率为 50%时，方法 5 导致估计值不够准确，而方法 1 至 3 则导致代理引入的偏差较小。在不同的域和不同的样本量下，偏差保持较低，但随着代理应答者比例的增加而增加。
我们的研究发现，在估计多个健康领域的 PRO 评分或回归估计值时，代理引入的偏差适中。即使样本量为 50，代理应答者的比例较大，这种偏差仍然很低。虽然当代理应答者的比例<20%时，这些方法中的许多方法都可以用于将代理纳入中风 PRO 研究，但在代理应答者的比例为 50%时，经调整的代理替代法导致的偏差较小。
