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2022
Journal Article
Title
Mortality factors in pancreatic surgery: A systematic review
Title Supplement
How important is the hospital volume?
Abstract
Background
How the extent of confounding adjustment impact (hospital) volume-outcome relationships in published studies on pancreatic cancer surgery is unknown.
Methods
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.
Results
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).
Conclusions
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.
How the extent of confounding adjustment impact (hospital) volume-outcome relationships in published studies on pancreatic cancer surgery is unknown.
Methods
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.
Results
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).
Conclusions
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.
Author(s)