Empirical treatment effectiveness models for binary outcomes

Medical Decision Making

Volumn 36, Issue 1, 2016, Pages 101-114

  Dalton, Jarrod E ^a   Dawson, Neal V ^b   Sessler, Daniel I ^a   Schold, Jesse D ^a   Love, Thomas E ^b   Kattan, Michael W ^a  

^a LERNER RESEARCH INSTITUTE   (United States)

^b METROHEALTH MEDICAL CENTER   (United States)

Author keywords

outcomes research; performance measurement; quality of care; vascular surgery

Indexed keywords

CLINICAL DECISION MAKING; COST BENEFIT ANALYSIS; ELECTRONIC HEALTH RECORD; HEART MUSCLE REVASCULARIZATION; HOSPITAL MORTALITY; HUMAN; MORTALITY; ODDS RATIO; OUTCOME ASSESSMENT; PROCEDURES; RANDOMIZED CONTROLLED TRIAL (TOPIC); STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

CLINICAL DECISION-MAKING; COST-BENEFIT ANALYSIS; ELECTRONIC HEALTH RECORDS; HOSPITAL MORTALITY; HUMANS; MODELS, STATISTICAL; MYOCARDIAL REVASCULARIZATION; ODDS RATIO; OUTCOME ASSESSMENT (HEALTH CARE); RANDOMIZED CONTROLLED TRIALS AS TOPIC;

EID: 84950145033     PISSN: 0272989X     EISSN: 1552681X     Source Type: Journal    
DOI: 10.1177/0272989X15578835     Document Type: Article

References (28)

1. Sox HC, Greenfield S,. Comparative effectiveness research: a report from the Institute of Medicine. Ann Intern Med. 2009; 151 (3): 203-5.
2. Rubin DB,. On the limitations of comparative effectiveness research. Stat Med. 2010; 29 (19): 1991-5.
3. Hillis LD, Smith PK, Anderson JL, et al. 2011 ACCF/AHA Guideline for Coronary Artery Bypass Graft Surgery: executive summary: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. 2011; 124 (23): 2610-42.
4. Levine GN, Bates ER, Blankenship JC, et al. 2011 ACCF/AHA/SCAI Guideline for Percutaneous Coronary Intervention: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines and the Society for Cardiovascular Angiography and Interventions. Circulation. 2011; 124 (23): e574-e651.
5. Kolh P, Windecker S, Alfonso F, et al. 2014 ESC/EACTS guidelines on myocardial revascularization: the Task Force on Myocardial Revascularization of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS) developed with the special contribution of the European Association of Percutaneous Cardiovascular Interventions (EAPCI). EuroIntervention. 2014; 46 (4): 517-92.
6. Efron B, Tibshirani R,. Improvements on cross-validation: the 632+ bootstrap method. J Am Stat Assoc. 1997; 92 (438): 548-60.
7. Hastie T, Tibshirani R, Friedman JH,. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. New York, NY: Springer; 2009.
8. Kohavi R,. A study of cross-validation and bootstrap for accuracy estimation and model selection. Paper presented at: The International Joint Conference on Artificial Intelligence; 1995 Aug 20-25; Montreal, QC, Canada.
9. Breiman L,. Random forests. Machine Learning. 2001; 45 (1): 5-32.
10. Zou H, Hastie T,. Regularization and variable selection via the elastic net. J R Stat Soc Ser B. 2005; 67 (2): 301-20.
11. Dalton JE, Glance LG, Mascha EJ, Ehrlinger J, Chamoun N, Sessler DI,. Impact of present-on-admission indicators on risk-adjusted hospital mortality measurement. Anesthesiology. 2013; 118 (6): 1298-306.
12. Harrell FE,. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. New York, NY: Springer; 2001.
13. Dalton JE,. Flexible recalibration of binary clinical prediction models. Stat Med. 2013; 32 (2): 282-9.
14. Russell LB,. Do we really value identified lives more highly than statistical lives? Med Decis Making. 2013; 34 (5): 556-9.
15. Epstein AJ, Polsky D, Yang F, Yang L, Groeneveld PW,. Coronary revascularization trends in the United States, 2001-2008. JAMA. 2011; 305 (17): 1769-76.
16. Rubin DB,. Causal inference using potential outcomes. J Am Stat Assoc. 2005; 100: 469.
17. Hingorani AD, van der Windt DA, Riley RD, et al. Prognosis research strategy (PROGRESS)4: stratified medicine research. BMJ. 2013; 346: e5793.
18. Bogardus ST Jr, Holmboe E, Jekel JF,. Perils, pitfalls, and possibilities in talking about medical risk. JAMA. 1999; 281 (11): 1037-41.
19. Steyerberg EW, Vickers AJ, Cook NR, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010; 21 (1): 128-38.
20. Kent DM, Rothwell PM, Ioannidis JP, Altman DG, Hayward RA,. Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal. Trials. 2010; 11 (1): 85.
21. Farooq V, van Klaveren D, Steyerberg EW, et al. Anatomical and clinical characteristics to guide decision making between coronary artery bypass surgery and percutaneous coronary intervention for individual patients: development and validation of SYNTAX score II. Lancet. 2013; 381 (9867): 639-50.
22. Serruys PW, Onuma Y, Garg S, et al. Assessment of the SYNTAX score in the Syntax study. EuroIntervention. 2009; 5 (1): 50-6.
23. Sianos G, Morel MA, Kappetein AP, et al. The SYNTAX score: an angiographic tool grading the complexity of coronary artery disease. EuroIntervention. 2005; 1 (2): 219-27.
24. Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R,. European system for cardiac operative risk evaluation (EuroSCORE). Eur J Cardiothorac Surg. 1999; 16 (1): 9-13.
25. Wu C, Hannan EL, Walford G, et al. A risk score to predict in-hospital mortality for percutaneous coronary interventions. J Am Coll Cardiol. 2006; 47 (3): 654-60.
26. Toumpoulis IK, Anagnostopoulos CE, Derose JJ Jr, Swistel DG,. The impact of deep sternal wound infection on long-term survival after coronary artery bypass grafting. Chest J. 2005; 127 (2): 464-71.
27. Cox DR,. Two further applications of a model for binary regression. Biometrika. 1958; 45 (3/4): 562-5.
28. Steyerberg EW,. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating. New York, NY: Springer; 2009.