Faculty of Medicine, University Hospital Brandenburg, Brandenburg Medical School Theodor Fontane, Brandenburg, Germany.
Martin Luther University Halle-Wittenberg, Institute of Medical Immunology, Halle, Germany; Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.
Int J Surg. 2022 May;101:106640. doi: 10.1016/j.ijsu.2022.106640. Epub 2022 May 4.
How the extent of confounding adjustment impact (hospital) volume-outcome relationships in published studies on pancreatic cancer surgery is unknown.
A systematic literature search was conducted for studies that investigated the relationship between volume and outcome using a risk adjustment procedure by querying the following databases: PubMed, Cochrane Central Register of Controlled Trials, Livivo, Medline and the International Clinical Trials Registry Platform (last query: 2020/09/16). Importance of risk-adjusting covariates were assessed by effect size (odds ratio, OR) and statistical significance. The impact of covariate adjustment on hospital (or surgeon) volume effects was analyzed by regression and meta-regression models.
We identified 87 studies (75 based on administrative data) with nearly 1 million patients undergoing pancreatic surgery that included in total 71 covariates for risk adjustment. Of these, 33 (47%) had statistically significant effects on short-term mortality and 23 (32%) did not, while for 15 (21%) factors neither effect size nor statistical significance were reported. The most important covariates for short term mortality were patient-specific factors. Concerning the covariates, single comorbidities (OR: 4.6, 95% CI: 3.3 to 6.3) had the strongest impact on mortality followed by hospital volume (OR: 2.9, 95% CI: 2.5 to 3.3) and the procedure (OR: 2.2, 95% CI: 1.9 to 2.5). Among the single comorbidities, coagulopathy (OR: 4.5, 95% CI: 2.8 to 7.2) and dementia (OR: 4.2, 95% CI: 2.2 to 8.0) had the strongest influence on mortality. The regression analysis showed a significant decrease hospital volume effect with an increasing number of covariates considered (OR: 0.06, 95% CI: 0.10 to -0.03, P < 0.001), while such a relationship was not observed for surgeon volume (P = 0.35).
This analysis demonstrated a significant inverse relationship between the extent of risk adjustment and the volume effect, suggesting the presence of unmeasured confounding and overestimation of volume effects. However, the conclusions are limited in that only the number of included covariates was considered, but not the effect size of the non-included covariates.
发表的胰腺癌手术研究中,混杂因素调整程度如何影响(医院)量效关系尚不清楚。
通过查询以下数据库,对研究使用风险调整程序调查体积与结果之间关系的文献进行系统的文献检索:PubMed、Cochrane 对照试验中心注册库、Livivo、Medline 和国际临床试验注册平台(最后一次查询:2020 年 9 月 16 日)。通过效应大小(比值比,OR)和统计显著性评估风险调整协变量的重要性。通过回归和荟萃回归模型分析协变量调整对医院(或外科医生)量效关系的影响。
我们确定了 87 项研究(75 项基于行政数据),共纳入近 100 万例接受胰腺手术的患者,其中共纳入 71 项风险调整协变量。其中,33 项(47%)对短期死亡率有统计学显著影响,23 项(32%)没有,而 15 项(21%)既没有报告效应大小也没有报告统计学显著性。对短期死亡率最重要的协变量是患者特异性因素。关于协变量,单一合并症(OR:4.6,95%CI:3.3 至 6.3)对死亡率的影响最大,其次是医院量(OR:2.9,95%CI:2.5 至 3.3)和手术方式(OR:2.2,95%CI:1.9 至 2.5)。在单一合并症中,凝血障碍(OR:4.5,95%CI:2.8 至 7.2)和痴呆(OR:4.2,95%CI:2.2 至 8.0)对死亡率的影响最大。回归分析显示,随着考虑的协变量数量的增加,医院量效关系呈显著下降趋势(OR:0.06,95%CI:0.10 至 -0.03,P<0.001),而外科医生量效关系则没有这种关系(P=0.35)。
本分析表明,风险调整程度与量效关系之间存在显著的反比关系,提示存在未测量的混杂因素和对量效关系的高估。然而,由于仅考虑了纳入协变量的数量,而未考虑未纳入协变量的效应大小,因此结论有限。