Software Tools

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• Pharmacoepidemiology Toolbox
  
• ‍Combined Comorbidity Score
• Sensitivity Analysis
• Clustered Permutation & Logrank Tests
• ‍Episheet
• Causal Contrasts
• British Columbia ChIPS
• Maternal Comorbidity Index
• Plasmode simulation framework
• Disease risk score matching in nested case control studies
• Propensity score fine stratification
• Removal of Ineligible Cases
• Claims-based Frailty Index
• Disease risk score calculation from Cox model
• A Medicare claims-based model for ejection fraction class prediction in heart failure
• Pediatric comorbidity index
• A Prediction Model to Identify Patients with High Electronic Health Record Data Completeness

Pharmacoepidemiology Toolbox including High-dimensional Propensity Score (hd-PS) Adjustment version 2

• Important Notes for Version 244 and Later — Please Read (.txt file)
  
• Rassen JA, Glynn RJ, Brookhart MA, Schneeweiss S. Covariate selection in high-dimensional propensity score analyses of treatment effects in small samples. Am J Epidemiol 2011 Jun 15; 173(12):1404-13. Epub 2011 May 20
• ‍Toolbox Download (.zipfile, version 2.20.18)
• ‍Important note on the implementation of the Bross formula in the updated hd-ps software
• Using the Pharmacoepi Toolbox in SAS Documentation (.pdf file)
• Toolbox Archive (previous versions of toolbox)
• R Code for high-dimensional propensity score: https://github.com/lendle/hdps

*Notification – There are restricted circumstances where the nearest neighbor macro does not identify all matches within caliper (e.g. when the cohort size is large and the c-statistic is low with few unique propensity score values). This issue will be corrected in the next version update. Until the next version is released, a workaround would be to re-run the macro on remaining unmatched patients until no more matches are found.

Combined Comorbidity Score for Claims Data

ICD-9-CM:
Gagne JJ, Glynn RJ, Avorn J, Levin R, Schneeweiss S. A combined comorbidity score predicted mortality in elderly patients better than existing scores.Journal of Clinical Epidemiology 2011;64(7):749-59.

ICD-10-CM:
Sun JW, Rogers JR, Her Q, Welch EC, Panozzo CA, Toh S, Gagne JJ. Adaptation and Validation of the Combined Comorbidity Score for ICD-10-CM. Medical Care. 2017 Dec 1;55(12):1046-51.
Table of ICD-10-CM codes (.doc)

Sensitivity Analysis

• Schneeweiss S. Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics. Pharmacoepidemiology & Drug Safety 2006 May. 15(5):291-303. (.pdf format)
• Sensitivity Analysis of Confounding 2020 (.xls format)
  

Clustered Permutation Test

• Program to Generate Example Data (SAS code) (.txt format)
  
• ‍Clustered Permutation Test Macro (SAS code) (.txt format)
• For documentation of the software see: Stedman MR, Gagnon DR, Lew RA, Solomon DH, Losina E, Brookhart MA. A SAS Macro for the Clustered Permutation Test. Computer Methods and Programs in Biomedicine. 95(2009) 89–94.

Clustered Logrank Test

• Stedman MR, Gagnon DR, Lew RA, Jung SH, Losina E, Brookhart MA. A SAS macro for a clustered logrank test. Comput Methods Programs Biomed. 2011 Apr 13. [Epub ahead of print]
• Example Data (.sas7bdat format)
  
• ‍Clustered Logrank Test Macro (SAS Code) (.txt format)

Episheet

Episheet by Ken Rothman (.xls format) – Spreadsheets for the Analysis of Epidemiologic Data

Causal Contrasts

• Readme: March 2006 (.txt format)
  
• ‍Causal.Comp.V1: March3006 (.xls format) — The Causal.Comp. Excel spreadsheet allows easy calculation of several summary estimates for an exposure of interest – outcome association in the presence of a dichotomous covariate which can be a confounder or not and an effect-measure modifier (multiplicative scale) or not. The spreadsheet should be used after reading:
• Sturmer T, Rothman KJ, Glynn RJ. Insights into different results from different causal contrasts in the presence of effect-measure modification. Pharmacoepidemiology & Drug Safety 2006 Oct. 15(10):698-709.

British Columbia Chart Insert Pilot Study (BC ChIPS)

• Price Speedometer (.pdf format)
  
• ‍Split & Save on Statins (.pdf format)
• ‍How do you split your cholesterol tablet? (.pdf format)

Maternal Comorbidity Index

Maternal Comorbidity Index Code

Plasmode simulation framework

• R Code and instructions for using the plasmode framework to create simulated data from a real cohort study
  
• An example using plasmode simulation with a real dataset
  
• ‍Plasmode simulation for the evaluation of pharmacoepidemiologic methods in complex healthcare databases
• ‍Plasmode R Package: https://cran.r-project.org/web/packages/Plasmode/index.html

Disease risk score matching in nested case control studies

• Desai RJ, Glynn RJ, Wang S, Gagne JJ. Performance of Disease Risk Score Matching in Nested Case-Control Studies: A Simulation Study. Am J Epidemiol. 2016 May; 183(10):949-57.
  
• nCC Sampling Macro (.text format)
  
• User Guide (pdf format)
• Example dataset (zip file)

Propensity score fine stratification

• Desai RJ, Rothman KJ, Bateman BT, Hernandez-Diaz S, Huybrechts KF. A Propensity-score-based Fine Stratification Approach for Confounding Adjustment When Exposure Is Infrequent. Epidemiology. 2017 03; 28(2):249-257. PMID: 27922533.
  
• ‍Propensity score fine stratification (dataverse)

Disease risk score calculation from Cox model

• Desai RJ, Wyss R, Jin Y, Bohn J, Toh S, Cosgrove A, Kennedy A, Kim J, Kim C, Ouellet-Hellstrom R, Karami S, Major JM, Niman A, Wang SV, Gagne JJ. Extension of Disease Risk Score-Based Confounding Adjustments for Multiple Outcomes of Interest: An Empirical Evaluation. Am J Epidemiol. 2018 Nov 01; 187(11):2439-2448. PMID: 29947726.
• DRS from Cox macro (.text format)

Removal of Ineligible Cases

Removal of Ineligible Cases Worksheet (.xls format)

Claims-based Frailty Index

• Kim DH, Schneeweiss S. Measuring Frailty Using Claims Data for Pharmacoepidemiologic Studies of Mortality in Older Adults: Evidence and Recommendations. Pharmacoepidemiol Drug Saf. 2014; 23: 891-901. doi: 10.1002/pds.3674. PMID: 24962929 PMCID: PMC4149846
• Kim DH, Schneeweiss S, Lipsitz LA, Glynn R, Rockwood K, Avorn J. Measuring Frailty in Medicare Data: Development and Validation of a Claims-Based Frailty Index. J Gerontol A Biol Sci Med Sci. 2018; 73: 980-987. doi: 10.1093/gerona/glx229. PMID: 29244057; PMCID: PMC6001883
• Kim DH, Glynn RJ, Avorn J, Lipsitz LA, Rockwood K, Pawar A, Schneeweiss S. Validation of a Claims-Based Frailty Index Against Physical Performance and Adverse Health Outcomes in the Health and Retirement Study. J Gerontol A Biol Sci Med Sci. 2019; 74: 1271-1276. doi: https://doi.org/10.1093/gerona/gly197. PMID: 30165612; PMCID: PMC6625579
• ‍Kim DH, Patorno E, Pawar A, Lee H, Schneeweiss S, Glynn RJ. Measuring Frailty in Administrative Claims Data: Comparative Performance of Four Claims-Based Frailty Measures in the United States Medicare Data. J Gerontol A Biol Sci Med Sci. 2019. doi: 10.1093/gerona/glz224. [Epub ahead of print] PMID: 31566201
• ‍Kim DH. Measuring Frailty in Health Care Databases for Clinical Care and Research. Ann Geriatr Med Res. 2020. doi: https://doi.org/10.4235/agmr.20.0002
• Frailty Index- SAS code Guide

A Medicare claims-based model for ejection fraction class prediction in heart failure

• Desai RJ, Lin KJ, Patorno E, et al. Development and Preliminary Validation of a Medicare Claims Based Model to Predict Left Ventricular Ejection Fraction Class in Patients With Heart Failure. Circulation: Cardiovascular Quality and Outcomes. 2018;11(12):e004700.
• EF prediction model user guide (pdf format)
• Model implementation (.text format)
• Score codes (.text format)

Pediatric comorbidity index

• Sun JW, Bourgeois FT, Haneuse S, Hernandez-Diaz S, Landon J, Bateman BT, Huybrechts KF. Development and Validation of a Pediatric Comorbidity Index. American Journal of Epidemiology. 2020; doi: 10.1093/aje/kwaa244
• Pediatric comorbidity index SAS code (.text format)

A Prediction Model to Identify Patients with High Electronic Health Data Completeness

• Lin KJ, Singer DE, Glynn RJ, Murphy SN, Lii J, Schneeweiss S. Identifying Patients with High Data Completeness to Improve Validity of Comparative Effectiveness Research in Electronic Health Records Data. Clin Pharmacol Ther. 2018;103(5):899-905.
• EHR Continuity without demographics (SAS code)