Individualized Absolute Risk Calculations for Persons with Multiple Chronic Conditions: Embracing Heterogeneity, Causality, and Competing Events
DOI:
https://doi.org/10.6000/1929-6029.2016.05.01.5Keywords:
Multiple chronic disease, heterogeneity, propensity scores, longitudinal study, absolute risk, competing outcomes, decision tools.Abstract
Approximately 75% of adults over the age of 65 years are affected by two or more chronic medical conditions. We provide a conceptual justification for individualized absolute risk calculators for competing patient-centered outcomes (PCO) (i.e. outcomes deemed important by patients) and patient reported outcomes (PRO) (i.e. outcomes patients report instead of physiologic test results). The absolute risk of an outcome is the probability that a person receiving a given treatment will experience that outcome within a pre-defined interval of time, during which they are simultaneously at risk for other competing outcomes. This allows for determination of the likelihood of a given outcome with and without a treatment. We posit that there are heterogeneity of treatment effects among patients with multiple chronic conditions (MCC) largely depends on those coexisting conditions.
We outline the development of an individualized absolute risk calculator for competing outcomes using propensity score methods that strengthen causal inference for specific treatments. Innovations include the key concept that any given outcome may or may not concur with any other outcome and that these competing outcomes do not necessarily preclude other outcomes. Patient characteristics and MCC will be the primary explanatory factors used in estimating the heterogeneity of treatment effects on PCO and PRO. This innovative method may have wide-spread application for determining individualized absolute risk calculations for competing outcomes. Knowing the probabilities of outcomes in absolute terms may help the burgeoning population of patients with MCC who face complex treatment decisions.
References
Multiple Chronic Conditions-A Strategic Framework: Washington DC: U.S. Department of Health and Human Services; 2010 [cited 2013 January 29, 2013].
Anderson G. Making the Case for Ongoing Care: Robert Wood Johnson Foundation; 2010 [cited 2013]. Available from: http://www.rwjf.org/en/research-publications/find-rwjf-research/2010/02/chronic-care.html
Wallace RB, Salive ME. The Dimensions of Multiple Chronic Conditions: Where Do We Go From Here? A Commentary on the Special Collection of Preventing Chronic Disease. Prev Chronic Dis 2013(10): E59. DOI: https://doi.org/10.5888/pcd10.130104
Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance. JAMA 2005; 294(6): 716-24. http://dx.doi.org/10.1001/jama.294.6.716 DOI: https://doi.org/10.1001/jama.294.6.716
Condelius A, Edberg AK, Jakobsson U, Hallberg IR. Hospital admissions among people 65+ related to multimorbidity, municipal and outpatient care. Arch Gerontol Geriatr 2008; 46(1): 41-55. http://dx.doi.org/10.1016/j.archger.2007.02.005 DOI: https://doi.org/10.1016/j.archger.2007.02.005
Laux G, Kuehlein T, Rosemann T, Szecsenyi J. Co- and multimorbidity patterns in primary care based on episodes of care: results from the German CONTENT project. BMC Health Serv Res 2008; 8: 14. http://dx.doi.org/10.1186/1472-6963-8-14 DOI: https://doi.org/10.1186/1472-6963-8-14
Tinetti ME, Bogardus ST, Jr., Agostini JV. Potential pitfalls of disease-specific guidelines for patients with multiple conditions. N Engl J Med 2004; 351(27): 2870-4. http://dx.doi.org/10.1056/NEJMsb042458 DOI: https://doi.org/10.1056/NEJMsb042458
Tinetti ME, Fried T. The end of the disease era. Am J Med 2004; 116(3): 179-85. http://dx.doi.org/10.1016/j.amjmed.2003.09.031 DOI: https://doi.org/10.1016/j.amjmed.2003.09.031
Tooth L, Hockey R, Byles J, Dobson A. Weighted multimorbidity indexes predicted mortality, health service use, and health-related quality of life in older women. J Clin Epidemiol 2008; 61(2): 151-9. http://dx.doi.org/10.1016/j.jclinepi.2007.05.015 DOI: https://doi.org/10.1016/j.jclinepi.2007.05.015
Boyd CM, Boult C, Shadmi E, Leff B, Brager R, Dunbar L, et al. Guided care for multimorbid older adults. Gerontologist 2007; 47(5): 697-704. http://dx.doi.org/10.1093/geront/47.5.697 DOI: https://doi.org/10.1093/geront/47.5.697
McCormick WC, Boling PA. Multimorbidity and a comprehensive Medicare care-coordination benefit. J Am Geriatr Soc 2005; 53(12): 2227-8. http://dx.doi.org/10.1111/j.1532-5415.2005.00504.x DOI: https://doi.org/10.1111/j.1532-5415.2005.00504.x
Muller-Tasch T, Peters-Klimm F, Schellberg D, Holzapfel N, Barth A, Junger J, et al. Depression is a major determinant of quality of life in patients with chronic systolic heart failure in general practice. J Card Fail 2007; 13(10): 818-24. http://dx.doi.org/10.1016/j.cardfail.2007.07.008 DOI: https://doi.org/10.1016/j.cardfail.2007.07.008
Noel PH, Frueh BC, Larme AC, Pugh JA. Collaborative care needs and preferences of primary care patients with multimorbidity. Health Expect 2005; 8(1): 54-63. http://dx.doi.org/10.1111/j.1369-7625.2004.00312.x DOI: https://doi.org/10.1111/j.1369-7625.2004.00312.x
Gross CP, Guo Z, McAvay GJ, Allore HG, Young M, Tinetti ME. Multimorbidity and survival in older persons with colorectal cancer. J Am Geriatr Soc 2006; 54(12): 1898-904. http://dx.doi.org/10.1111/j.1532-5415.2006.00973.x DOI: https://doi.org/10.1111/j.1532-5415.2006.00973.x
Fortin M, Bravo G, Hudon C, Lapointe L, Dubois MF, Almirall J. Psychological distress and multimorbidity in primary care. Ann Fam Med 2006; 4(5): 417-22. http://dx.doi.org/10.1370/afm.528 DOI: https://doi.org/10.1370/afm.528
Fortin M, Lapointe L, Hudon C, Vanasse A, Ntetu AL, Maltais D. Multimorbidity and quality of life in primary care: a systematic review. Health Qual Life Outcomes 2004; 2: 51. http://dx.doi.org/10.1186/1477-7525-2-51 DOI: https://doi.org/10.1186/1477-7525-2-51
Fried LP, Kronmal RA, Newman AB, Bild DE, Mittelmark MB, Polak JF, et al. Risk factors for 5-year mortality in older adults: the Cardiovascular Health Study. JAMA 1998; 279(8): 585-92. http://dx.doi.org/10.1001/jama.279.8.585 DOI: https://doi.org/10.1001/jama.279.8.585
John R, Kerby DS, Hennessy CH. Patterns and impact of comorbidity and multimorbidity among community-resident American Indian elders. Gerontologist 2003; 43(5): 649-60. http://dx.doi.org/10.1093/geront/43.5.649 DOI: https://doi.org/10.1093/geront/43.5.649
Kadam UT, Croft PR. Clinical multimorbidity and physical function in older adults: a record and health status linkage study in general practice. Fam Pract 2007; 24(5): 412-9. http://dx.doi.org/10.1093/fampra/cmm049 DOI: https://doi.org/10.1093/fampra/cmm049
Lee SJ, Lindquist K, Segal MR, Covinsky KE. Development and validation of a prognostic index for 4-year mortality in older adults. JAMA 2006; 295(7): 801-8. http://dx.doi.org/10.1001/jama.295.7.801 DOI: https://doi.org/10.1001/jama.295.7.801
Menotti A, Mulder I, Nissinen A, Giampaoli S, Feskens EJ, Kromhout D. Prevalence of morbidity and multimorbidity in elderly male populations and their impact on 10-year all-cause mortality: The FINE study (Finland, Italy, Netherlands, Elderly). J Clin Epidemiol 2001; 54(7): 680-6. http://dx.doi.org/10.1016/S0895-4356(00)00368-1 DOI: https://doi.org/10.1016/S0895-4356(00)00368-1
Bibbins-Domingo K, Lin F, Vittinghoff E, Barrett-Connor E, Grady D, Shlipak MG. Renal insufficiency as an independent predictor of mortality among women with heart failure. J Am Coll Cardiol 2004; 44(8): 1593-600. http://dx.doi.org/10.1016/j.jacc.2004.07.040 DOI: https://doi.org/10.1016/j.jacc.2004.07.040
Ettinger WH, Jr., Fried LP, Harris T, Shemanski L, Schulz R, Robbins J. Self-reported causes of physical disability in older people: the Cardiovascular Health Study. CHS Collaborative Research Group. J Am Geriatr Soc 1994; 42(10): 1035-44. http://dx.doi.org/10.1111/j.1532-5415.1994.tb06206.x DOI: https://doi.org/10.1111/j.1532-5415.1994.tb06206.x
Felker GM, Gattis WA, Leimberger JD, Adams KF, Cuffe MS, Gheorghiade M, et al. Usefulness of anemia as a predictor of death and rehospitalization in patients with decompensated heart failure. Am J Cardiol 2003; 92(5): 625-8. http://dx.doi.org/10.1016/S0002-9149(03)00740-9 DOI: https://doi.org/10.1016/S0002-9149(03)00740-9
Fortin M, Dubois MF, Hudon C, Soubhi H, Almirall J. Multimorbidity and quality of life: a closer look. Health Qual Life Outcomes 2007; 5: 52. http://dx.doi.org/10.1186/1477-7525-5-52 DOI: https://doi.org/10.1186/1477-7525-5-52
Goulet JL, Fultz SL, Rimland D, Butt A, Gibert C, Rodriguez-Barradas M, et al. Aging and infectious diseases: do patterns of comorbidity vary by HIV status, age, and HIV severity? Clin Infect Dis 2007; 45(12): 1593-601. http://dx.doi.org/10.1086/523577 DOI: https://doi.org/10.1086/523577
Mehta RH, Dabbous OH, Granger CB, Kuznetsova P, Kline-Rogers EM, Anderson FA, Jr., et al. Comparison of outcomes of patients with acute coronary syndromes with and without atrial fibrillation. Am J Cardiol 2003; 92(9): 1031-6. http://dx.doi.org/10.1016/j.amjcard.2003.06.001 DOI: https://doi.org/10.1016/j.amjcard.2003.06.001
Whitson HE, Cousins SW, Burchett BM, Hybels CF, Pieper CF, Cohen HJ. The combined effect of visual impairment and cognitive impairment on disability in older people. J Am Geriatr Soc 2007; 55(6): 885-91. http://dx.doi.org/10.1111/j.1532-5415.2007.01093.x DOI: https://doi.org/10.1111/j.1532-5415.2007.01093.x
Whooley MA. Depression and cardiovascular disease: healing the broken-hearted. JAMA 2006; 295(24): 2874-81. http://dx.doi.org/10.1001/jama.295.24.2874 DOI: https://doi.org/10.1001/jama.295.24.2874
Marengoni A, Winblad B, Karp A, Fratiglioni L. Prevalence of chronic diseases and multimorbidity among the elderly population in Sweden. Am J Public Health 2008; 98(7): 1198-200. http://dx.doi.org/10.2105/AJPH.2007.121137 DOI: https://doi.org/10.2105/AJPH.2007.121137
Fried TR, McGraw S, Agostini JV, Tinetti ME. Views of older persons with multiple morbidities on competing outcomes and clinical decision-making. J Am Geriatr Soc 2008; 56(10): 1839-44. http://dx.doi.org/10.1111/j.1532-5415.2008.01923.x DOI: https://doi.org/10.1111/j.1532-5415.2008.01923.x
Tinetti ME, McAvay GJ, Fried TR, Allore HG, Salmon JC, Foody JM, et al. Health outcome priorities among competing cardiovascular, fall injury, and medication-related symptom outcomes. J Am Geriatr Soc 2008; 56(8): 1409-16. http://dx.doi.org/10.1111/j.1532-5415.2008.01815.x DOI: https://doi.org/10.1111/j.1532-5415.2008.01815.x
Tinetti ME, McAvay GJ, Fried TR, Foody JM, Bianco L, Ginter S, et al. Development of a tool for eliciting patient priority from among competing cardiovascular disease, medication-symptoms, and fall injury outcomes. J Am Geriatr Soc 2008; 56(4): 730-6. http://dx.doi.org/10.1111/j.1532-5415.2007.01627.x DOI: https://doi.org/10.1111/j.1532-5415.2007.01627.x
Crossing the quality chasm: A new health system for the 21st century. Washington, D.C.: National Academies Press; 2001.
Cauley JA, Ensrud KE. Considering competing risks . . . Not all black and white. Arch Intern Med 2008; 168(8): 793-5. http://dx.doi.org/10.1001/archinte.168.8.793 DOI: https://doi.org/10.1001/archinte.168.8.793
Fried TR, Bradley EH, Towle VR, Allore H. Understanding the treatment preferences of seriously ill patients. N Engl J Med 2002; 346(14): 1061-6. http://dx.doi.org/10.1056/NEJMsa012528 DOI: https://doi.org/10.1056/NEJMsa012528
McNeil BJ, Pauker SG, Sox HC, Jr., Tversky A. On the elicitation of preferences for alternative therapies. N Engl J Med 1982; 306(21): 1259-62. http://dx.doi.org/10.1056/NEJM198205273062103 DOI: https://doi.org/10.1056/NEJM198205273062103
Gill TM, Allore HG, Gahbauer EA, Murphy TE. Change in disability after hospitalization or restricted activity in older persons. JAMA 2010; 304(17): 1919-28. http://dx.doi.org/10.1001/jama.2010.1568 DOI: https://doi.org/10.1001/jama.2010.1568
Gill TM, Allore HG, Holford TR, Guo Z. Hospitalization, restricted activity, and the development of disability among older persons. JAMA 2004; 292(17): 2115-24. http://dx.doi.org/10.1001/jama.292.17.2115 DOI: https://doi.org/10.1001/jama.292.17.2115
Gill TM, Gahbauer EA, Murphy TE, Han L, Allore HG. Risk factors and precipitants of long-term disability in community mobility: a cohort study of older persons. Ann Intern Med 2012; 156(2): 131-40. http://dx.doi.org/10.7326/0003-4819-156-2-201201170-00009 DOI: https://doi.org/10.7326/0003-4819-156-2-201201170-00009
Brookhart MA, Schneeweiss S, Rothman KJ, Glynn RJ, Avorn J, Sturmer T. Variable selection for propensity score models. Am J Epidemiol 2006; 163(12): 1149-56. http://dx.doi.org/10.1093/aje/kwj149 DOI: https://doi.org/10.1093/aje/kwj149
Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983; 70: 41-55. http://dx.doi.org/10.1093/biomet/70.1.41 DOI: https://doi.org/10.1093/biomet/70.1.41
Feng WW, Jun Y, Xu R. A method/macro based on propensity score and Mahalanobis distance to reduce bias in treatment comparison in observational study2005. Available from: www.lexjansen.com/pharmasug/2006/publichealthre-search/pr05.pdf
Vaz Fragoso CA, Concato J, McAvay G, Van Ness PH, Gill TM. Respiratory impairment and COPD hospitalisation in older persons: a competing risk analysis. Eur Respir J 2012; 40(1): 37-44. http://dx.doi.org/10.1183/09031936.00128711 DOI: https://doi.org/10.1183/09031936.00128711
Medical Expenditure Panel Survey [cited 2013 January 28, 2013]. Available from: www.meps.ahrq.gov/mepsweb
National Health Interview Survey [January 28, 2013]. Available from: http://www.cdc.gov/nchs/nhis.htm
Rosenbaum PR, Rubin DB. The bias due to incomplete matching. Biometrics 1985; 41(1): 103-16. http://dx.doi.org/10.2307/2530647 DOI: https://doi.org/10.2307/2530647
Braitman LE, Rosenbaum PR. Rare outcomes, common treatments: analytic strategies using propensity scores. Ann Intern Med 2002; 137(8): 693-5. http://dx.doi.org/10.7326/0003-4819-137-8-200210150-00015 DOI: https://doi.org/10.7326/0003-4819-137-8-200210150-00015
Foody JM, Cole CR, Blackstone EH, Lauer MS. A propensity analysis of cigarette smoking and mortality with consideration of the effects of alcohol. Am J Cardiol 2001; 87(6): 706-11. http://dx.doi.org/10.1016/S0002-9149(00)01487-9 DOI: https://doi.org/10.1016/S0002-9149(00)01487-9
Larson EB. Evidence, guidelines, performance incentives, complexity, and old people: a clinician's dilemma. J Am Geriatr Soc 2009; 57(2): 353-4. http://dx.doi.org/10.1111/j.1532-5415.2008.02125.x DOI: https://doi.org/10.1111/j.1532-5415.2008.02125.x
Rubin DB. Estimating causal effects from large data sets using propensity scores. Ann Intern Med 1997; 127(8 Pt 2): 757-63. http://dx.doi.org/10.7326/0003-4819-127-8_Part_2-199710151-00064 DOI: https://doi.org/10.7326/0003-4819-127-8_Part_2-199710151-00064
Shah BR, Laupacis A, Hux JE, Austin PC. Propensity score methods gave similar results to traditional regression modeling in observational studies: a systematic review. J Clin Epidemiol 2005; 58(6): 550-9. http://dx.doi.org/10.1016/j.jclinepi.2004.10.016 DOI: https://doi.org/10.1016/j.jclinepi.2004.10.016
Giordano SH, Kuo YF, Duan Z, Hortobagyi GN, Freeman J, Goodwin JS. Limits of observational data in determining outcomes from cancer therapy. Cancer 2008; 112(11): 2456-66. http://dx.doi.org/10.1002/cncr.23452 DOI: https://doi.org/10.1002/cncr.23452
Glesby MJ, Hoover DR. Survivor treatment selection bias in observational studies: examples from the AIDS literature. Ann Intern Med 1996; 124(11): 999-1005. http://dx.doi.org/10.7326/0003-4819-124-11-199606010-00008 DOI: https://doi.org/10.7326/0003-4819-124-11-199606010-00008
Glynn RJ, Schneeweiss S, Sturmer T. Indications for propensity scores and review of their use in pharmacoepidemiology. Basic Clin Pharmacol Toxicol 2006; 98(3): 253-9. http://dx.doi.org/10.1111/j.1742-7843.2006.pto_293.x DOI: https://doi.org/10.1111/j.1742-7843.2006.pto_293.x
Laupacis A, Mamdani M. Observational studies of treatment effectiveness: some cautions. Ann Intern Med 2004; 140(11): 923-4. http://dx.doi.org/10.7326/0003-4819-140-11-200406010-00014 DOI: https://doi.org/10.7326/0003-4819-140-11-200406010-00014
Benichou J, Gail MH. Estimates of absolute cause-specific risk in cohort studies. Biometrics 1990; 46(3): 813-26. http://dx.doi.org/10.2307/2532098 DOI: https://doi.org/10.2307/2532098
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2016 Heather Allore, Gail McAvay, Carlos A. Vaz Fragoso, Terrence E. Murphy
This work is licensed under a Creative Commons Attribution 4.0 International License.
Policy for Journals/Articles with Open Access
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
Policy for Journals / Manuscript with Paid Access
Authors who publish with this journal agree to the following terms:
- Publisher retain copyright .
- Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work .
