Dimension reduction and shrinkage methods for high dimensional disease risk scores in historical data

Emerging Themes in Epidemiology

Volumn 13, Issue 1, 2016, Pages

  Kumamaru, Hiraku ^a,b   Schneeweiss, Sebastian ^a   Glynn, Robert J ^a   Setoguchi, Soko ^c   Gagne, Joshua J ^a  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b UNIVERSITY OF TOKYO   (Japan)

^c DUKE CLINICAL RESEARCH INSTITUTE   (United States)

Author keywords

Comparative study; Confounding; Disease risk score; High dimensional propensity score; Historical data; Shrinkage

Indexed keywords

CYCLOOXYGENASE 2 INHIBITOR; DABIGATRAN; NONSTEROID ANTIINFLAMMATORY AGENT; WARFARIN;

ADULT; AGED; ANALYTIC METHOD; ARTICLE; COHORT ANALYSIS; DATA ANALYSIS; DIMENSION REDUCTION AND SHRINKAGE METHOD; DRUG MARKETING; DRUG SAFETY; FEASIBILITY STUDY; FEMALE; GASTROINTESTINAL HEMORRHAGE; HUMAN; MAJOR CLINICAL STUDY; MALE; OUTCOME ASSESSMENT; PRINCIPAL COMPONENT ANALYSIS; RISK ASSESSMENT;

EID: 84962429855     PISSN: None     EISSN: 17427622     Source Type: Journal    
DOI: 10.1186/s12982-016-0047-x     Document Type: Article

References (31)

1. Gagne JJ, Rassen JA, Choudhry NK, Bohn RL, Patrick AR, Sridhar G, Daniel GW, Liu J, Schneeweiss S. Near-real-time monitoring of new drugs: an application comparing prasugrel versus clopidogrel. Drug Saf. 2014;37:151-61.
2. Schneeweiss S, Gagne JJ, Glynn RJ, Ruhl M, Rassen JA. Assessing the comparative effectiveness of newly marketed medications: methodological challenges and implications for drug development. Clin Pharmacol Ther. 2011;90:777-90.
3. Schneeweiss S, Huybrechts KF, Gagne JJ. Interpreting the quality of health care database studies on the comparative effectiveness of oral anticoagulants in routine care. Comp Eff Res. 2013;3:33-41.
4. Harrell FE, Lee KL, Califf RM, Pryor DB, Rosati RA. Regression modelling strategies for improved prognostic prediction. Stat Med. 1984;3:143-52.
5. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41-55.
6. Rubin DB. Estimating causal effects from large data sets using propensity scores. Ann Intern Med. 1997;127(8 Pt 2):757-63.
7. Sturmer T, Joshi M, Glynn RJ, Avorn J, Rothman KJ, Schneeweiss S, Stürmer T, Joshi M, Glynn RJ, Avorn J, Rothman KJ, Schneeweiss S. A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. J Clin Epidemiol. 2006;59:437-47.
8. Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology. 2009;20:512-22.
9. Glynn RJ, Gagne JJ, Schneeweiss S. Role of disease risk scores in comparative effectiveness research with emerging therapies. Pharmacoepidemiol Drug Saf. 2012;21:138-47.
10. 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;173:1404-13.
11. Hansen BB. The prognostic analogue of the propensity score. Biometrika. 2008;95:481-8.
12. Pomeroy SL, Tamayo P, Gaasenbeek M, Sturla LM, Angelo M, McLaughlin ME, Kim JYH, Goumnerova LC, Black PM, Lau C, Allen JC, Zagzag D, Olson JM, Curran T, Wetmore C, Biegel JA, Poggio T, Mukherjee S, Rifkin R, Califano A, Stolovitzky G, Louis DN, Mesirov JP, Lander ES, Golub TR. Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature. 2002;415:436-42.
13. Riedelsheimer C, Czedik-Eysenberg A, Grieder C, Lisec J, Technow F, Sulpice R, Altmann T, Stitt M, Willmitzer L, Melchinger AE. Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat Genet. 2012;44:217-20.
14. Wang D, SalahElBasyoni I, Stephen Baenziger P, Crossa J, Eskridge KM, Dweikat I. Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations. Heredity (Edinb). 2012;109:313-9.
15. January CT, Wann LS, Alpert JS, Calkins H, Cleveland JC, Cigarroa JE, Conti JB, Ellinor PT, Ezekowitz MD, Field ME, Murray KT, Sacco RL, Stevenson WG, Tchou PJ, Tracy CM, Yancy CW. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol. 2014;64:e1-e76.
16. Connolly S, Ezekowitz M, Reilly PA, Themeles E, Varrone J, Wang S, Alings M, Xavier D, Zhu J, Diaz R, Lewis BS, Darius H, Diener H, Joyner CD, Wallentin L, Committee RS. Dabigatran versus warfarin in patients with atrial fibrillation. New. 2009;361:1139-51.
17. Solomon DH, Schneeweiss S, Glynn RJ, Kiyota Y, Levin R, Mogun H, Avorn J. Relationship between selective cyclooxygenase-2 inhibitors and acute myocardial infarction in older adults. Circulation. 2004;109:2068-73.
18. Wahl PM, Rodgers K, Schneeweiss S, Gage BF, Butler J, Wilmer C, Nash M, Esper G, Gitlin N, Osborn N, Short LJ, Bohn RL. Validation of claims-based diagnostic and procedure codes for cardiovascular and gastrointestinal serious adverse events in a commercially-insured population. Pharmacoepidemiol Drug Saf. 2010;19(February):596-603.
19. Watson DJ, Harper SE, Zhao PL, Quan H, Bolognese JA, Simon TJ. Gastrointestinal tolerability of the selective cyclooxygenase-2 (COX-2) inhibitor rofecoxib compared with nonselective COX-1 and COX-2 inhibitors in osteoarthritis. Arch Intern Med. 2000;160:2998-3003.
20. Moore RA, Derry S, Makinson GT, Mcquay HJ. Tolerability and adverse events in clinical trials of celecoxib in osteoarthritis and rheumatoid arthritis: systematic review and meta-analysis of information from company clinical trial reports. Arthritis Res Ther. 2005;7:R644-65.
21. Silverstein FE, Faich G, Goldstein JL, Simon LS, Pincus T, Whelton A, Stenson WF, Burr AM, Zhao WW, Kent JD, Lefkowith JB, Geis GS. Gastrointestinal toxicity with celecoxib versus nonsteroidal anti-inflammatory drugs for osteoarthritis and rheumatoid arthritis. J Am Med Assoc. 2000;284:1247-55.
22. Bombardier C, Laine L, Reicin A, Shapiro D, Burgos-Vargas R, Davis B, Day R, Ferraz MB, Hawkey CJ, Hochberg M, Kvein TK, Schnitzer T, Hospital MS, De Medicina EP, Sciences S, Hospital D. Comparison of upper gastrointestinal toxicity of rofecoxib and naproxen in patients with rheumatoid arthritis. N Engl J Med. 2000;343:1520-8.
23. Pisters R, Lane DA, Nieuwlaat R, de Vos CB, Crijns HJGM, Lip GYH. A novel user-friendly score (HAS-BLED) to assess 1-year risk of major bleeding in patients with atrial fibrillation: the Euro Heart Survey. Chest. 2010;138:1093-100.
24. Gagne JJ, Glynn RJ, Avorn J, Levin R, Schneeweiss S. A combined comorbidity score predicted mortality in elderly patients better than existing scores. J Clin Epidemiol. 2011;64:749-59.
25. Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010;33:1-22.
26. Arbogast PG, Ray WA. Performance of disease risk scores, propensity scores, and traditional multivariable outcome regression in the presence of multiple confounders. Am J Epidemiol. 2011;174:613-20.
27. Arbogast PG, Ray WA. Use of disease risk scores in pharmacoepidemiologic studies. Stat Methods Med Res. 2009;18:67-80.
28. Hansen BB. Bias reduction in observational studies via prognosis scores. In: Tech Rep #441 Stat Dept Univ Michigan. 2006. p. 1-29.
29. Francis Cook E, Goldman L. Performance of tests of significance based on stratification by a multivariate confounder score or by a propensity score. J Clin Epidemiol. 1989;42:317-24.
30. Stürmer T, Schneeweiss S, Brookhart MA, Rothman KJ, Avorn J, Glynn RJ. Analytic strategies to adjust confounding using exposure propensity scores and disease risk scores: nonsteroidal antiinflammatory drugs and short-term mortality in the elderly. Am J Epidemiol. 2005;161:891-8.
31. Leacy FP, Stuart EA. On the joint use of propensity and prognostic scores in estimation of the average treatment effect on the treated: a simulation study. Stat Med. 2013;33(October):3488-508.