scholarly journals Covariate Balance as a Quality Indicator for Propensity Score Analysis

2021 ◽  
Author(s):  
Yusuf KARA ◽  
Akihito KAMATA ◽  
Elisa GALLEGOS ◽  
Chalie PATARAPİCHAYATHAM ◽  
Cornelis J. POTGİETER
Keyword(s):  
Propensity Score ◽  
Quality Indicator ◽  
Propensity Score Analysis ◽  
Covariate Balance ◽  
Score Analysis

scholarly journals Assessing covariate balance when using the generalized propensity score with quantitative or continuous exposures

2018 ◽  
Vol 28 (5) ◽  
pp. 1365-1377 ◽  
Author(s):  
Peter C Austin
Keyword(s):  
Propensity Score ◽  
Propensity Score Analysis ◽  
Balance Assessment ◽  
Propensity Score Method ◽  
Propensity Score Methods ◽  
Covariate Balance ◽  
Crucial Component ◽  
Score Analysis ◽  
Generalized Propensity Score ◽  
Using Data

Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score was initially developed for use with binary exposures (e.g., active treatment vs. control). The generalized propensity score is an extension of the propensity score for use with quantitative exposures (e.g., dose or quantity of medication, income, years of education). A crucial component of any propensity score analysis is that of balance assessment. This entails assessing the degree to which conditioning on the propensity score (via matching, weighting, or stratification) has balanced measured baseline covariates between exposure groups. Methods for balance assessment have been well described and are frequently implemented when using the propensity score with binary exposures. However, there is a paucity of information on how to assess baseline covariate balance when using the generalized propensity score. We describe how methods based on the standardized difference can be adapted for use with quantitative exposures when using the generalized propensity score. We also describe a method based on assessing the correlation between the quantitative exposure and each covariate in the sample when weighted using generalized propensity score -based weights. We conducted a series of Monte Carlo simulations to evaluate the performance of these methods. We also compared two different methods of estimating the generalized propensity score: ordinary least squared regression and the covariate balancing propensity score method. We illustrate the application of these methods using data on patients hospitalized with a heart attack with the quantitative exposure being creatinine level.

Efficacy of variceal embolisation in patients with TIPS implantation: a propensity score analysis

2018 ◽  
Vol 56 (01) ◽  
pp. E2-E89
Author(s):  
M Giesler ◽  
D Bettinger ◽  
M Rössle ◽  
R Thimme ◽  
M Schultheiss
Keyword(s):  
Propensity Score ◽  
Propensity Score Analysis ◽  
Score Analysis

scholarly journals Morbidity and mortality of lobectomy or pneumonectomy after neoadjuvant treatment: an analysis from the ESTS database

2019 ◽  
Author(s):  
Alessandro Brunelli ◽  
Gaetano Rocco ◽  
Zalan Szanto ◽  
Pascal Thomas ◽  
Pierre Emmanuel Falcoz
Keyword(s):  
Neoadjuvant Chemotherapy ◽  
Propensity Score ◽  
Propensity Score Analysis ◽  
Bronchopleural Fistula ◽  
Neoadjuvant Treatment ◽  
Mortality Rates ◽  
Induction Treatment ◽  
Score Analysis ◽  
Cardiopulmonary Complications ◽  
Lung Resections

Abstract OBJECTIVES To evaluate the postoperative complications and 30-day mortality rates associated with neoadjuvant chemotherapy before major anatomic lung resections registered in the European Society of Thoracic Surgeons (ESTS) database. METHODS Retrospective analysis on 52 982 anatomic lung resections registered in the ESTS database (July 2007–31 December 2017) (6587 pneumonectomies and 46 395 lobectomies); 5143 patients received neoadjuvant treatment (9.7%) (3993 chemotherapy alone and 1150 chemoradiotherapy). To adjust for possible confounders, a propensity case-matched analysis was performed. The postoperative outcomes (morbidity and 30-day mortality) of matched patients with and without induction treatment were compared. RESULTS 8.2% of all patients undergoing lobectomies and 20% of all patients undergoing pneumonectomies received induction treatment. Lobectomy analysis: propensity score analysis yielded 3824 pairs of patients with and without induction treatment. The incidence of cardiopulmonary complications was higher in the neoadjuvant group (626 patients, 16% vs 446 patients, 12%, P < 0.001), but 30-day mortality rates were similar (71 patients, 1.9% vs 75 patients, 2.0%, P = 0.73). The incidence of bronchopleural fistula and prolonged air leak >5 days were similar between the 2 groups (neoadjuvant: 0.5% vs 0.4%, P = 0.87; 9.2% vs 9.9%, P = 0.27). Pneumonectomy analysis: propensity score analysis yielded 1312 pairs of patients with and without induction treatment. The incidence of cardiopulmonary complications was higher in the treated patients compared to those without neoadjuvant treatment (neoadjuvant 275 cases, 21% vs 18%, P = 0.030). However, the 30-day mortality was similar between the matched groups (neoadjuvant 68 cases, 5.2% vs 5.3%, P = 0.86). Finally, the incidence of bronchopleural fistula was also similar between the 2 groups (neoadjuvant 1.8% vs 1.4%, P = 0.44). CONCLUSIONS Neoadjuvant chemotherapy is not associated with an increased perioperative risk after either lobectomy or pneumonectomy, warranting a more liberal use of this approach for patients with locally advanced operable lung cancer.

scholarly journals Procedural times in early non-intubated VATS program - a propensity score analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Isabella Metelmann ◽  
Johannes Broschewitz ◽  
Uta-Carolin Pietsch ◽  
Gerald Huschak ◽  
Uwe Eichfeld ◽  
...  
Keyword(s):  
Propensity Score ◽  
Surgical Procedure ◽  
Recovery Time ◽  
Propensity Score Analysis ◽  
Wedge Resection ◽  
University Hospital ◽  
Implementation Phase ◽  
Score Analysis ◽  
Significant Difference ◽  
Procedural Time

Abstract Background Non-intubated video-assisted thoracic surgery (NiVATS) has been introduced to surgical medicine in order to reduce the invasiveness of anesthetic procedures and avoid adverse effects of intubation and one-lung ventilation (OLV). The aim of this study is to determine the time effectiveness of a NiVATS program compared to conventional OLV. Methods This retrospective analysis included all patients in Leipzig University Hospital that needed minor VATS surgery between November 2016 and October 2019 constituting a NiVATS (n = 67) and an OLV (n = 36) group. Perioperative data was matched via propensity score analysis, identifying two comparable groups with 23 patients. Matched pairs were compared via t-Test. Results Patients in NiVATS and OLV group show no significant differences other than the type of surgical procedure performed. Wedge resection was performed significantly more often under NiVATS conditions than with OLV (p = 0,043). Recovery time was significantly reduced by 7 min (p = 0,000) in the NiVATS group. There was no significant difference in the time for induction of anesthesia, duration of surgical procedure or overall procedural time. Conclusions Recovery time was significantly shorter in NiVATS, but this effect disappeared when extrapolated to total procedural time. Even during the implementation phase of NiVATS programs, no extension of procedural times occurs.

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