Cited by 737Frailty in Older AdultsPalliative Care and End-of-Life IssuesInsurance, Mortality, Demography, Risk Management

The DOI matches its Crossref record; 73 of the 74 references it cites were found in a registry or an index.

Prognostic Indices for Older Adults: A Systematic Review

Open access

Yourman, Lindsey C., Lee, Sei J., Schonberg, Mara A., Widera, Eric W., Smith, Alexander K.·2012·JAMA

DOI 10.1001/jama.2011.1966PMC PMC3792853

Open this paper in CoChat — free account

Abstract

CONTEXT: To better target services to those who may benefit, many guidelines recommend incorporating life expectancy into clinical decisions. OBJECTIVE: To assess the quality and limitations of prognostic indices for mortality in older adults through systematic review. DATA SOURCES: We searched MEDLINE, EMBASE, Cochrane, and Google Scholar from their inception through November 2011. STUDY SELECTION: We included indices if they were validated and predicted absolute risk of mortality in patients whose average age was 60 years or older. We excluded indices that estimated intensive care unit, disease-specific, or in-hospital mortality. DATA EXTRACTION: For each prognostic index, we extracted data on clinical setting, potential for bias, generalizability, and accuracy. RESULTS: We reviewed 21,593 titles to identify 16 indices that predict risk of mortality from 6 months to 5 years for older adults in a variety of clinical settings: the community (6 indices), nursing home (2 indices), and hospital (8 indices). At least 1 measure of transportability (the index is accurate in more than 1 population) was tested for all but 3 indices. By our measures, no study was free from potential bias. Although 13 indices had C statistics of 0.70 or greater, none of the indices had C statistics of 0.90 or greater. Only 2 indices were independently validated by investigators who were not involved in the index's development. CONCLUSION: We identified several indices for predicting overall mortality in different patient groups; future studies need to independently test their accuracy in heterogeneous populations and their ability to improve clinical outcomes before their widespread use can be recommended.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1001/jama.2011.1966

Cites

73 of 73 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation
Charlson, M. E., Pompei, P., Ales, K. L., & MacKenzie, C. R. (1987) · Journal of Chronic Diseases · doi:10.1016/0021-9681(87)90171-8 · Cited by 49,742
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
Comorbidity measures for use with administrative data.
Elixhauser, A., Steiner, C., Harris, D. R., & Coffey, R. M. (1998) · Medical Care · doi:10.1097/00005650-199801000-00004 · Cited by 9,921
Assessing the Performance of Prediction Models: A Framework for Traditional and Novel Measures
Steyerberg, E. W., Vickers, A. J., Cook, N. R., Gerds, T., Gonen, M., Obuchowski, N., Pencina, M. J., & Kattan, M. W. (2010) · Epidemiology · doi:10.1097/ede.0b013e3181c30fb2 · Cited by 5,170
The TIMI Risk Score for Unstable Angina/Non–ST Elevation MI
Antman, E. M., Cohen, M. C., Bernink, P. J. L. M., McCabe, C. H., Horacek, T., Papuchis, G., Mautner, B., Corbalán, R., Radley, D. R., & Braunwald, E. (2000) · JAMA · doi:10.1001/jama.284.7.835 · Cited by 3,221
Treatment of hypertension in patients 80 years of age or older
Beckett, N. S., Peters, R., Fletcher, A. E., Staessen, J. A., Liu, L., Dumitrascu, D., Stoyanovsky, V., Antikainen, R. L., Nikitin, Y., Anderson, C., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0801369 · Cited by 3,092
A modification of the elixhauser comorbidity measures into a point system for hospital death using administrative data
van Walraven, C., Austin, P. C., Jennings, A., Quan, H., & Forster, A. J. (2009) · Medical Care · doi:10.1097/mlr.0b013e31819432e5 · Cited by 2,200
Validation of the Framingham Coronary Heart Disease Prediction Scores: Results of a Multiple Ethnic Groups Investigation
D'Agostino, R. B., Grundy, S., Sullivan, L. M., Wilson, P., & for the CHD Risk Prediction Group (2001) · JAMA · doi:10.1001/jama.286.2.180 · Cited by 2,108
Presentation adapting a clinical comorbidity index for use with ICD-9-CM administrative data: Differing perspectives
Romano, P. S., Roos, L. L., & Jollis, J. G. (1993) · Journal of Clinical Epidemiology · doi:10.1016/0895-4356(93)90103-8 · Cited by 1,717
Evaluation of the Quality of Prognosis Studies in Systematic Reviews
Hayden, J. A., Côté, P., & Bombardier, C. (2006) · Annals of Internal Medicine · doi:10.7326/0003-4819-144-6-200603210-00010 · Cited by 1,452

Show all 74 references

Research works printed but not linked: 2

[7]Laupacis A Sekar N Stiell IG Clinical prediction rules. A review and suggested modifications of methodological standards JAMA 1997 277 6 488 494 9020274
[51]Einhorn HJ Hogarth RM Bell DE Raiffa H Tversky A Behavioral decision theory: process of judgement and choice Decision-Making: Descriptive, Normative, and Prescriptive Interactions Cambridge, MA Cambridge University Press 1988 113 146

Sorted by citations

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration
Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147
2014 AHA/ACC Guideline for the Management of Patients With Non–ST-Elevation Acute Coronary Syndromes
Amsterdam, E. A., Wenger, N. K., Brindis, R. G., Casey, D. E., Ganiats, T. G., Holmes, D. R., Jaffe, A. S., Jneid, H., Kelly, R. F., Kontos, M. C., et al. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2014.09.017 · Cited by 3,595
Updated standardized endpoint definitions for transcatheter aortic valve implantation: the Valve Academic Research Consortium-2 consensus document (VARC-2)
Kappetein, A. P., Head, S. J., Généreux, P., Piazza, N., Mieghem, N. M. V., Blackstone, E., Brott, T., Cohen, D., Cutlip, D. E., van Es, G., et al. (2012) · doi:10.48350/15011 · Cited by 3,375
International Society of Geriatric Oncology Consensus on Geriatric Assessment in Older Patients With Cancer
Wildiers, H. P. M. W., Heeren, P., Puts, M. T. E., Topinková, E., Janssen-Heijnen, M. L. G., Extermann, M., Falandry, C., Artz, A. S., Brain, E. G. C., Colloca, G. A., et al. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2013.54.8347 · Cited by 1,854
Updated Standardized Endpoint Definitions for Transcatheter Aortic Valve Implantation
Kappetein, A. P., Head, S. J., Généreux, P., Piazza, N., Mieghem, N. M. V., Blackstone, E. H., Brott, T. G., Cohen, D. J., Cutlip, D. E., van Es, G., et al. (2012) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2012.09.001 · Cited by 1,677
“Prognostic indices of life expectancy may play a central role in moving beyond arbitrary age-based cut-offs (14).”
Breast Cancer Screening for Women at Average Risk
Oeffinger, K. C., Fontham, E. T. H., Etzioni, R., Herzig, A. H., Michaelson, J. S., Shih, Y. T., Walter, L. C., Church, T. R., Flowers, C. R., LaMonte, S. J., et al. (2015) · JAMA · doi:10.1001/jama.2015.12783 · Cited by 1,706
Updated standardized endpoint definitions for transcatheter aortic valve implantation: the Valve Academic Research Consortium-2 consensus document (VARC-2)
Kappetein, A. P., Head, S. J., Généreux, P., Piazza, N., van Mieghem, N. M., Blackstone, E. H., Brott, T. G., Cohen, D. J., Cutlip, D. E., van Es, G.-A., et al. (2012) · European Journal of Cardio-Thoracic Surgery · doi:10.1093/ejcts/ezs533 · Cited by 1,631
2021 ACC/AHA/SCAI Guideline for Coronary Artery Revascularization
Lawton, J. S., Tamis‐Holland, J. E., Bangalore, S., Bates, E., Beckie, T. M., Bischoff, J. M., Bittl, J. A., Cohen, M. G., DiMaio, J. M., Don, C. W., et al. (2021) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2021.09.006 · Cited by 1,691
Practical assessment and management of vulnerabilities in older patients receiving chemotherapy: ASCO guideline for geriatric oncology
Mohile, S. G., Dale, W., Somerfield, M. R., Schonberg, M. A., Boyd, C. M., Burhenn, P. S., Canin, B., Cohen, H. J., Holmes, H. M., Hopkins, J. O., et al. (2018) · Journal of Clinical Oncology · doi:10.1200/jco.2018.78.8687 · Cited by 1,479
Self-citation
Communication About Serious Illness Care Goals: A Review and Synthesis of Best Practices
Bernacki, R. E., & Block, S. D. (2014) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2014.5271 · Cited by 1,422
2021 ACC/AHA/SCAI Guideline for Coronary Artery Revascularization: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines
Lawton, J. S., Tamis‐Holland, J. E., Bangalore, S., Bates, E. R., Beckie, T. M., Bischoff, J. M., Bittl, J. A., Cohen, M. G., DiMaio, J. M., Don, C. W., et al. (2021) · Circulation · doi:10.1161/cir.0000000000001038 · Cited by 1,349
Diabetes in Older Adults
Kirkman, M. S., Briscoe, V. J., Clark, N., Florez, H., Haas, L. B., Halter, J. B., Huang, E. S., Korytkowski, M. T., Munshi, M. N., Odegard, P. S., et al. (2012) · Diabetes Care · doi:10.2337/dc12-1801 · Cited by 1,274
2014 AHA/ACC Guideline for the Management of Patients With Non–ST-Elevation Acute Coronary Syndromes: Executive Summary
Amsterdam, E. A., WENGER, N. K., Brindis, R. G., Casey, D. E., Ganiats, T. G., Holmes, D. R., Jaffe, A. S., Jneid, H. M., Kelly, R. F., Kontos, M. C., et al. (2014) · Circulation · doi:10.1161/cir.0000000000000133 · Cited by 1,266
“Bivalirudin is useful as an anticoagulant with or without prior treatment with UFH in patients with NSTE-ACS undergoing PCI (154, 213-217).”
BackgroundMethod
2014 AHA/ACC Guideline for the Management of Patients With Non–ST-Elevation Acute Coronary Syndromes: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines
Amsterdam, E. A., Wenger, N. K., Brindis, R. G., Casey, D. E., Ganiats, T. G., Holmes, D. R., Jaffe, A. S., Jneid, H., Kelly, R. F., Kontos, M. C., et al. (2014) · Circulation · doi:10.1161/cir.0000000000000134 · Cited by 1,059
Updated standardized endpoint definitions for transcatheter aortic valve implantation: the Valve Academic Research Consortium-2 consensus document†
Kappetein, A. P., Head, S. J., Généreux, P., Piazza, N., Mieghem, N. M. V., Blackstone, E. H., Brott, T. G., Cohen, D. J., Cutlip, D. E., van Es, G., et al. (2012) · European Heart Journal · doi:10.1093/eurheartj/ehs255 · Cited by 1,045
“Prognostic indices of life expectancy may play a central role in moving beyond arbitrary age-based cut-offs [14].”
Background
Updated standardized endpoint definitions for transcatheter aortic valve implantation: The Valve Academic Research Consortium-2 consensus document
Kappetein, A. P., Head, S. J., Généreux, P., Piazza, N., Mieghem, N. M. V., Blackstone, E. H., Brott, T. G., Cohen, D. J., Cutlip, D. E., van Es, G., et al. (2012) · Journal of Thoracic and Cardiovascular Surgery · doi:10.1016/j.jtcvs.2012.09.002 · Cited by 925
“Prognostic indices of life expectancy may play a central role in moving beyond arbitrary age-based cut-offs [14].”
2014 AHA/ACC Guideline for the Management of Patients With Non–ST-Elevation Acute Coronary Syndromes: Executive Summary
Amsterdam, E. A., WENGER, N. K., Brindis, R. G., Casey, D. E., Ganiats, T. G., Holmes, D. R., Jaffe, A. S., Jneid, H. M., Kelly, R. F., Kontos, M. C., et al. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2014.09.016 · Cited by 782
Cancer screening in the United States, 2017: A review of current American Cancer Society guidelines and current issues in cancer screening
Smith, R. A., Andrews, K. S., Brooks, D. D., Fedewa, S. A., Manassaram‐Baptiste, D., Saslow, D., Brawley, O. W., & Wender, R. C. (2017) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.21392 · Cited by 733
“In applying clinical judgment about longevity, clinicians should use mortality indices that incorporate age, comorbidities, and functional status.(27,28) In addition, older women should be provided opportunities for individualized decision making that considers potential benefits and harms and incorporates health prio…”
Method
Cancer screening in the United States, 2019: A review of current American Cancer Society guidelines and current issues in cancer screening
Smith, R. A., Andrews, K. S., Brooks, D. D., Fedewa, S. A., Manassaram‐Baptiste, D., Saslow, D., & Wender, R. C. (2019) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.21557 · Cited by 747
Guiding Principles for the Care of Older Adults with Multimorbidity: An Approach for Clinicians
American Geriatrics Society Expert Panel on the Care of Older Adults with Multimorbidity (2012) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2012.04188.x · Cited by 681
“The specifics about which prognostic measure to include and what prognostic information to share with patients and families are part of the total integrated process of decision-making, in conjunction with an evaluation of the evidence and patient-stated preferences.(88) When attempting to integrate prognosis into clin…”
BackgroundMethod
Cancer screening in the United States, 2018: A review of current American Cancer Society guidelines and current issues in cancer screening
Smith, R. A., Andrews, K. S., Brooks, D. D., Fedewa, S. A., Manassaram‐Baptiste, D., Saslow, D., Brawley, O. W., & Wender, R. C. (2018) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.21446 · Cited by 579
“In applying clinical judgement about longevity, clinicians should use mortality indices that incorporate age, comorbidities, and functional status.(25,26) In addition, women should be provided opportunities for individualized decision making to consider the potential benefits and harms and incorporate health prioritie…”
Method
Diabetes in Older Adults: A Consensus Report
Sue Kirkman, M., Briscoe, V. J., Clark, N., Florez, H., Haas, L. B., Halter, J. B., Huang, E. S., Korytkowski, M. T., Munshi, M. N., Odegard, P. S., et al. (2012) · Journal of the American Geriatrics Society · doi:10.1111/jgs.12035 · Cited by 548
Cancer screening in the United States, 2014: A review of current American Cancer Society guidelines and current issues in cancer screening
Smith, R. A., Manassaram‐Baptiste, D., Brooks, D. D., Cokkinides, V. E., Doroshenk, M., Saslow, D., Wender, R. C., & Brawley, O. W. (2014) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.21212 · Cited by 480
External validation of new risk prediction models is infrequent and reveals worse prognostic discrimination
Siontis, G. C. M., Tzoulaki, I., Castaldi, P. J., & Ioannidis, J. P. A. (2014) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2014.09.007 · Cited by 473
“Recently published systematic reviews of studies in prognostic research field have raised concerns about the proper validation and reporting strategies of new risk models [2,75,76].”
Background
Three Decades of Comprehensive Geriatric Assessment: Evidence Coming From Different Healthcare Settings and Specific Clinical Conditions
Pilotto, A., Cella, A., Pilotto, A., Daragjati, J., Veronese, N., Musacchio, C., Mello, A. M., Logroscino, G., Padovani, A., Prete, C., et al. (2017) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2016.11.004 · Cited by 483
Updated standardized endpoint definitions for transcatheter aortic valve implantation: the Valve Academic Research Consortium-2 consensus document#
Kappetein, A. P., Head, S. J., Généreux, P., Piazza, N., Mieghem, N. M. V., Blackstone, E. H., Brott, T. G., Cohen, D. J., Cutlip, D. E., van Es, G., et al. (2012) · EuroIntervention · doi:10.4244/eijv8i7a121 · Cited by 455
5-Year mortality predictors in 498,103 UK Biobank participants: a prospective population-based study.
Ganna, A., & Ingelsson, E. (2015) · The Lancet · doi:10.1016/s0140-6736(15)60175-1 · Cited by 411
Functional versus chronological age: geriatric assessments to guide decision making in older patients with cancer
Soto‐Pérez‐de‐Celis, E., Li, D., Yuan, Y., Lau, Y. M., & Hurria, A. (2018) · The Lancet Oncology · doi:10.1016/s1470-2045(18)30348-6 · Cited by 412
A multidimensional approach to frailty in older people
Pilotto, A., Custodero, C., Maggi, S., Polidori, M. C., Veronese, N., & Ferrucci, L. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101047 · Cited by 400
“This instrument has been applied in several cohorts of older adults with specific acute and chronic diseases, showing always excellent calibration, reproducibility and accuracy in stratifying population according the risk of short and long-term mortality (Dent et al., 2016; Yourman et al., 2012).”
Method
Cancer statistics for adults aged 85 years and older, 2019
DeSantis, C. E., Miller, K. D., Dale, W., Mohile, S. G., Cohen, H. J., Leach, C. R., Goding Sauer, A., Jemal, A., & Siegel, R. L. (2019) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21577 · Cited by 370
Preoperative Assessment of the Older Patient
Oresanya, L. B., Lyons, W. L., & Finlayson, E. V. A. (2014) · JAMA · doi:10.1001/jama.2014.4573 · Cited by 344
“Chrispal et al, 201054 Hip fracture 81 ≥60 In-hospital 17 (21) Cognitive impairment 4 (24) OR 16.”
Screening for lung cancer: 2023 guideline update from the American Cancer Society
Wolf, A. M. D., Oeffinger, K. C., Shih, Y. T., Walter, L. C., Church, T. R., Fontham, E. T. H., Elkin, E. B., Etzioni, R., Guerra, C. E., Perkins, R. B., et al. (2023) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.21811 · Cited by 326
Patient‐Centered Care for Older Adults with Multiple Chronic Conditions: A Stepwise Approach from the American Geriatrics Society
American Geriatrics Society Expert Panel on the Care of Older Adults with Multimorbidity (2012) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2012.04187.x · Cited by 316
“Decisions can be prioritized based on life expectancy or other outcomes(41) and categorized as short-term (within 1 year), midterm (within 5 years), and long-term (beyond 5 years).(47) Individuals with limited life expectancy would focus on relevant short-term decisions such as intensity of glucose monitoring and cont…”
Background
Too much medicine in older people? Deprescribing through shared decision making
Jansen, J., Naganathan, V., Carter, S. M., McLachlan, A. J., Nickel, B., Irwig, L., Bonner, C., Doust, J. A., Colvin, J., Heaney, A., et al. (2016) · BMJ · doi:10.1136/bmj.i2893 · Cited by 309
STOPPFrail (Screening Tool of Older Persons Prescriptions in Frail adults with limited life expectancy): consensus validation
Lavan, A. H., Gallagher, P., Parsons, C., & O’Mahony, D. (2017) · Age and Ageing · doi:10.1093/ageing/afx005 · Cited by 310
“Since the most consistent predictors of mortality are co-morbidities and functional impairment [29], our de ﬁ nition of patients who are appropriate for deprescrib-ing according to STOPPFrail criteria was based on these essential indicators, rather than the presence of speci ﬁ c diseases, such as…”
Background
Cancer Screening and Early Detection in the 21st Century
Loud, J. T., & Murphy, J. (2017) · Seminars in Oncology Nursing · doi:10.1016/j.soncn.2017.02.002 · Cited by 292
“Future research will address the utility of these tools across all cancer screening recommendations to identify those who will benefit most from screening and those most likely to be harmed.(35)”
Method
Half Of Older Americans Seen In Emergency Department In Last Month Of Life; Most Admitted To Hospital, And Many Die There
Smith, A. K., McCarthy, E. P., Weber, E. J., Cenzer, I. S., Boscardin, W. J., Fisher, J., & Covinsky, K. E. (2012) · Health Affairs · doi:10.1377/hlthaff.2011.0922 · Cited by 272
Self-citation
Practice Bulletin Number 179: Breast Cancer Risk Assessment and Screening in Average-Risk Women
(2017) · Obstetrics and Gynecology · doi:10.1097/aog.0000000000002158 · Cited by 259
Screening Mammography in Older Women
Walter, L. C., & Schonberg, M. A. (2014) · JAMA · doi:10.1001/jama.2014.2834 · Cited by 245
Self-citation
Uncertainty — The Other Side of Prognosis
Smith, A. K., White, D. B., & Arnold, R. M. (2013) · New England Journal of Medicine · doi:10.1056/nejmp1303295 · Cited by 232
Self-citation
Time lag to benefit after screening for breast and colorectal cancer: meta-analysis of survival data from the United States, Sweden, United Kingdom, and Denmark
Lee, S. J., Boscardin, W. J., Stijacic‐Cenzer, I., Conell‐Price, J., O'Brien, S., & Walter, L. C. (2012) · BMJ · doi:10.1136/bmj.e8441 · Cited by 227
Self-citation
Predictive Accuracy of the Veterans Aging Cohort Study Index for Mortality With HIV Infection
Justice, A. C., Modur, S. P., Tate, J. P., Althoff, K. N., Jacobson, L. P., Gebo, K. A., Kitahata, M. M., Horberg, M. A., Brooks, J. T., Buchacz, K. A., et al. (2012) · JAIDS Journal of Acquired Immune Deficiency Syndromes · doi:10.1097/qai.0b013e31827df36c · Cited by 222
“Importantly, the discrimination of the VACS index rivals that of indices in clinical use including the Framingham index(13) and those recommended for use among geriatric patients.(14) Nevertheless, prognostic indices developed in one sample [those within the Veterans Affairs Healthcare System (VA)] may not generalize…”
BackgroundMethodInfluential
Incorporating Lag Time to Benefit Into Prevention Decisions for Older Adults
Lee, S. J., Leipzig, R. M., & Walter, L. C. (2013) · JAMA · doi:10.1001/jama.2013.282612 · Cited by 205
“A general approach involves the following: (1) estimate the patient’s life expectancy; (2) estimate the preventive intervention’s lag time to benefit; (3A) if life expectancy is much greater than lag time to benefit, the intervention may help and should generally be recommended; (3B) if life expectancy is much less th…”
Self-citation
An internationally generalizable risk index for mortality after one year of antiretroviral therapy
Tate, J. P., Justice, A. C., Hughes, M. D., Bonnet, F., Reiss, P., Mocroft, A., Nattermann, J., Lampe, F. C., Bucher, H. C., Sterling, T. R., et al. (2012) · AIDS · doi:10.1097/qad.0b013e32835b8c7f · Cited by 201
“71 in women) [30] and many indices recommended for geriatric populations [27].”
Background
Identifying patients with chronic conditions in need of palliative care in the general population: development of the NECPAL tool and preliminary prevalence rates in Catalonia
Gómez‐Batiste, X., Martínez-Muñoz, M., Blay, C., Amblàs-Novellas, J., Vila, L. C., Costa, X., Villanueva, A., Espaulella, J., Espinosa, J., Figuerola, M., et al. (2012) · BMJ Supportive & Palliative Care · doi:10.1136/bmjspcare-2012-000211 · Cited by 193
American Geriatrics Society Identifies Five Things That Healthcare Providers and Patients Should Question
Workgroup, A. C. W. (2013) · Journal of the American Geriatrics Society · doi:10.1111/jgs.12226 · Cited by 192
Self-Rated Health and Long-Term Prognosis of Depression
Ambresin, G., Chondros, P., Dowrick, C. F., Herrman, H., & Gunn, J. M. (2014) · The Annals of Family Medicine · doi:10.1370/afm.1562 · Cited by 195
The Central Role of Prognosis in Clinical Decision Making
Gill, T. M. (2012) · JAMA · doi:10.1001/jama.2011.1992 · Cited by 181
“A single estimate of life expectancy, for example, would allow a physician to advise an older patient about a large array of clinical decisions, such as whether to discontinue breast cancer screening or forego tight glycemic control for diabetes mellitus, as noted in Table 1 of the review by Yourman et al.1 The omissi…”
COVID-19 in Italy: Ageism and Decision Making in a Pandemic
Cesari, M., & Proietti, M. (2020) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2020.03.025 · Cited by 187
Age-specific changes in intrinsic breast cancer subtypes: a focus on older women
Jenkins, E. O., Deal, A. M., Anders, C. K., Prat, A., Perou, C. M., Carey, L. A., & Muss, H. B. (2014) · The Oncologist · doi:10.1634/theoncologist.2014-0184 · Cited by 165
Predictive modeling of U.S. health care spending in late life
Liran Einav, B., Finkelstein, A. N., Mullainathan, S., & Obermeyer, Z. (2018) · Science · doi:10.1126/science.aar5045 · Cited by 164
Deprescribing in older people approaching end-of-life: development and validation of STOPPFrail version 2
Curtin, D., Gallagher, P., & O’Mahony, D. (2020) · Age and Ageing · doi:10.1093/ageing/afaa159 · Cited by 164
Cancer Screening Rates in Individuals With Different Life Expectancies
Royce, T. J., Hendrix, L. H., Stokes, W. A., Allen, I. M., & Chen, R. C. (2014) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2014.3895 · Cited by 162
“Married 3902 (49) 3788 (44) 2166 (35) 1350 (32) 11 206 (41)”
Pitfalls in Communication That Lead to Nonbeneficial Emergency Surgery in Elderly Patients With Serious Illness
Cooper, Z. R., Courtwright, A., Karlage, A., Gawande, A. A., & Block, S. D. (2014) · Annals of Surgery · doi:10.1097/sla.0000000000000721 · Cited by 161
Predicting 10-Year Mortality for Older Adults
Cruz, M. L., Covinsky, K. E., Widera, E., Stijacic‐Cenzer, I., & Lee, S. J. (2013) · JAMA · doi:10.1001/jama.2013.1184 · Cited by 157
“However, most mortality indices have focused on short-term risk ( 5 years).(3,4) We examined whether our previously developed 4-year mortality index(5) accurately predicted 10-year mortality.”
Self-citation
Precision radiology: predicting longevity using feature engineering and deep learning methods in a radiomics framework
Oakden-Rayner, L., Carneiro, G., Bessen, T., Nascimento, J. C., Bradley, A. P., & Palmer, L. J. (2017) · Scientific Reports · doi:10.1038/s41598-017-01931-w · Cited by 154
Utility of the NECPAL CCOMS-ICO © tool and the Surprise Question as screening tools for early palliative care and to predict mortality in patients with advanced chronic conditions: A cohort study
Gómez‐Batiste, X., Martínez-Muñoz, M., Blay, C., Amblàs-Novellas, J., Vila, L. C., Costa, X., Espaulella, J., Villanueva, A., Oller, R., Martori, J. C., et al. (2016) · Palliative Medicine · doi:10.1177/0269216316676647 · Cited by 163
Personalizing Age of Cancer Screening Cessation Based on Comorbid Conditions: Model Estimates of Harms and Benefits
Lansdorp‐Vogelaar, I., Gulati, R., Mariotto, A. B., Schechter, C. B., de Carvalho, T. M., Knudsen, A. B., van Ravesteyn, N. T., Heijnsdijk, E. A. M., Pabiniak, C. J., van Ballegooijen, M., et al. (2014) · Annals of Internal Medicine · doi:10.7326/m13-2867 · Cited by 149
Population-based screening for cancer: hope and hype
Shieh, Y., Eklund, M., Sawaya, G. F., Black, W. C., Kramer, B. S., & Esserman, L. J. (2016) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.50 · Cited by 152
Rationalizing Prescribing for Older Patients with Multimorbidity: Considering Time to Benefit
Holmes, H. M., Min, L. C., Yee, M., Varadhan, R., Basran, J., Dale, W., & Boyd, C. M. (2013) · Drugs & Aging · doi:10.1007/s40266-013-0095-7 · Cited by 151
“Life expectancy can be estimated using various risk tools available [58] or global measures of reserve such as functional status or frailty [59, 60].”
Deep Learning to Assess Long-term Mortality From Chest Radiographs
Lu, M. T., Ivanov, A., Mayrhofer, T., Hosny, A., Aerts, H. J. W. L., & Hoffmann, U. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.7416 · Cited by 140
Cardiovascular Disease Risk Prediction in the HIV Outpatient Study
Thompson‐Paul, A. M., Lichtenstein, K. A., Armon, C., Palella, F. J., Skarbinski, J., Chmiel, J. S., Hart, R. L. D., Wei, S. C., Loustalot, F. V., Brooks, J. T., et al. (2016) · Clinical Infectious Diseases · doi:10.1093/cid/ciw615 · Cited by 141
Participation of the Elderly Population in Clinical Trials: Barriers and Solutions
Denson, A. C., & Mahipal, A. (2014) · Cancer Control · doi:10.1177/107327481402100305 · Cited by 142
Strategic Targeting of Advance Care Planning Interventions
Billings, J. A., & Bernacki, R. (2014) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2013.14384 · Cited by 135
Just ask: discussing goals of care with patients in hospital with serious illness
You, J. J., Fowler, R., & Heyland, D. K. (2013) · Canadian Medical Association Journal · doi:10.1503/cmaj.121274 · Cited by 131
A Framework for Crafting Clinical Practice Guidelines That Are Relevant to the Care and Management of People with Multimorbidity
Uhlig, K., Leff, B., Kent, D., Dy, S., Brunnhuber, K., Burgers, J. S., Greenfield, S., Guyatt, G., High, K., Leipzig, R., et al. (2014) · Journal of General Internal Medicine · doi:10.1007/s11606-013-2659-y · Cited by 158
Estimating and communicating prognosis in advanced neurologic disease
Holloway, R. G., Gramling, R. E., & Kelly, A. G. (2013) · Neurology · doi:10.1212/wnl.0b013e318282509c · Cited by 125
“A recent systematic review of non–disease-based prognostic indices for older adults concluded significant limitations in the current evidence and ability to apply them to patients.(30) d.”
Background
Changes in a Frailty Index and Association with Mortality
Shi, S., Olivieri‐Mui, B. L., McCarthy, E. P., & Kim, D. H. (2020) · Journal of the American Geriatrics Society · doi:10.1111/jgs.17002 · Cited by 119
Performance of Four Frailty Classifications in Older Patients With Cancer: Prospective Elderly Cancer Patients Cohort Study
Ferrat, É., Paillaud, É., Caillet, P., Laurent, M., Tournigand, C., Lagrange, J., Droz, J., Balducci, L., Audureau, É., Canouï‐Poitrine, F., et al. (2017) · Journal of Clinical Oncology · doi:10.1200/jco.2016.69.3143 · Cited by 121
“89 suggest moderate, good, and very good discrimination, respectively.(26) Higher D statistic values indicate better discrimination; no threshold is available.”
Background
Comprehensive and Integrated Palliative Care for People With Advanced Chronic Conditions: An Update From Several European Initiatives and Recommendations for Policy
Gómez‐Batiste, X., Murray, S. A., Thomas, K., Blay, C., Boyd, K. J., Moine, S., Gignon, M., den Eynden, B. V., Leysen, B., Wens, J., et al. (2016) · Journal of Pain and Symptom Management · doi:10.1016/j.jpainsymman.2016.10.361 · Cited by 123
“Among diverse parameters(39), the surprise question(40) and most of the individual parameters used in the existing tools, such as advanced frailty(41), functional decline(42), nutritional decline(43), cognitive decline(44), geriatric syndromes(45), multi-morbidity(46), and resource use of acute beds or emergency admis…”
Background
Tools for Deprescribing in Frail Older Persons and Those with Limited Life Expectancy: A Systematic Review
Thompson, W., Lundby, C., Graabæk, T., Nielsen, D. S., Ryg, J., Søndergaard, J., & Pottegård, A. (2018) · Journal of the American Geriatrics Society · doi:10.1111/jgs.15616 · Cited by 124
Identifying patients with advanced chronic conditions for a progressive palliative care approach: a cross-sectional study of prognostic indicators related to end-of-life trajectories
Amblàs-Novellas, J., Murray, S. A., Espaulella, J., Martori, J. C., Oller, R., Martínez-Muñoz, M., Molist‐Brunet, N., Blay, C., & Gómez‐Batiste, X. (2016) · BMJ Open · doi:10.1136/bmjopen-2016-012340 · Cited by 120
Treatment of Nonfatal Conditions at the End of Life
Linos, E., Parvataneni, R., Stuart, S. E., Boscardin, W. J., Landefeld, C. S., & Chren, M. (2013) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2013.639 · Cited by 110
“The rationale for these criteria is that they indicate LLE: a person 85 years old in the United States has a median life expectancy of approximately 5 years,(14) and a Charlson Comorbidity Index of 3 or higher indicates poorest survival and has been used to define poor prognosis.(15,16)”
Diet Quality Scores and Prediction of All-Cause, Cardiovascular and Cancer Mortality in a Pan-European Cohort Study
Lassale, C. M., Gunter, M. J., Romaguera, D., Peelen, L. M., van der Schouw, Y. T., Beulens, J. W. J., Freisling, H., Muller, D. C., Ferrari, P., Huybrechts, I., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0159025 · Cited by 112
Development and Validation of a Deep Learning Algorithm for Mortality Prediction in Selecting Patients With Dementia for Earlier Palliative Care Interventions
Wang, L., Sha, L., Lakin, J. R., Bynum, J., Bates, D. W., Hong, P., & Zhou, L. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.6972 · Cited by 105
Deprescribing for older patients
Frank, C., & Weir, E. L. (2014) · Canadian Medical Association Journal · doi:10.1503/cmaj.131873 · Cited by 108
Antidiabetic Medications and Polypharmacy
Peron, E. P., Ogbonna, K. C., & Donohoe, K. L. (2014) · Clinics in Geriatric Medicine · doi:10.1016/j.cger.2014.08.017 · Cited by 109
Polypharmacy in chronic diseases–Reduction of Inappropriate Medication and Adverse drug events in older populations by electronic Decision Support (PRIMA-eDS): study protocol for a randomized controlled trial
Sönnichsen, A. C., Trampisch, U. S., Rieckert, A., Piccoliori, G., Vögele, A., Flamm, M., Johansson, T., Esmail, A., Reeves, D., Löffler, C., et al. (2016) · Trials · doi:10.1186/s13063-016-1177-8 · Cited by 108
“son in the population aged 75 years or older [43].”
Background
Nonantiretroviral polypharmacy and adverse health outcomes among HIV-infected and uninfected individuals
Justice, A. C., Gordon, K. S., Skanderson, M., Edelman, E. J., Akgün, K. M., Gibert, C. L., Re, V. L., Rimland, D., Womack, J. A., Wyatt, C. M., et al. (2018) · AIDS · doi:10.1097/qad.0000000000001756 · Cited by 100
“exceeds the discrimination of prior indices validated among older individuals [26].”
Background
Prediction of Recovery, Dependence or Death in Elders Who Become Disabled During Hospitalization
Barnes, D. E., Mehta, K. M., Boscardin, W. J., Fortinsky, R. H., Palmer, R. M., Kirby, K. A., & Landefeld, C. S. (2012) · Journal of General Internal Medicine · doi:10.1007/s11606-012-2226-y · Cited by 99
Use of machine learning in geriatric clinical care for chronic diseases: a systematic literature review
Choudhury, A., Renjilian, E., & Asan, O. (2020) · JAMIA Open · doi:10.1093/jamiaopen/ooaa034 · Cited by 94
Risk prediction in the community: A systematic review of case-finding instruments that predict adverse healthcare outcomes in community-dwelling older adults
O’Caoimh, R., Cornally, N., Weathers, E., O'Sullivan, R., Fitzgerald, C., Orfila, F., Clarnette, R., Paúl, C., & Molloy, D. W. (2015) · Maturitas · doi:10.1016/j.maturitas.2015.03.009 · Cited by 89
“Only five of the 23 instruments were externally validated, a common criticism of current risk-prediction instruments [15].”
Background
Good end-of-life care in nursing home according to the family carers’ perspective: A systematic review of qualitative findings
Gonella, S., Basso, I., Marinis, M. G. D., Campagna, S., & Giulio, P. D. (2019) · Palliative Medicine · doi:10.1177/0269216319840275 · Cited by 92
American Geriatrics Society Identifies Another Five Things That Healthcare Providers and Patients Should Question
Workgroup, A. C. W. (2014) · Journal of the American Geriatrics Society · doi:10.1111/jgs.12770 · Cited by 93
“org and the ePrognosis cancer screening application (available for free at the Apple App Store) can help clinicians estimate prognoses and guide discussions with individuals and their caregivers about cancer screening.(10,25) Although people continue to believe in the effectiveness of cancer screening even in situatio…”
Background
Survival Prognosis in Very Old Adults
Thinggaard, M., McGue, M. K., Jeune, B., Osler, M., Vaupel, J. W., & Christensen, K. (2016) · Journal of the American Geriatrics Society · doi:10.1111/jgs.13838 · Cited by 90
“Simpler screening tools exist, but the have mostly been validated in people aged 70 to 80.(10,11) For nonagenarians, being able to rise from a chair without using hands and having an MMSE score of 28 or greater, the average remaining lifespan was 1.”
Method
Unmet needs, health policies, and actions during the COVID-19 pandemic: a report from six European countries
Miralles, O., Sánchez‐Rodríguez, D., Marco, E., Annweiler, C., Baztan, A., Betancor, É., Cambra, A., Cesari, M., Gómez, B. J. F., Gąsowski, J., et al. (2020) · European Geriatric Medicine · doi:10.1007/s41999-020-00415-x · Cited by 87
Multidimensional Prognostic Index Predicts Mortality and Length of Stay During Hospitalization in the Older Patients: A Multicenter Prospective Study
Volpato, S., Bazzano, S., Fontana, A., Ferrucci, L., & Pilotto, A. (2014) · The Journals of Gerontology Series A · doi:10.1093/gerona/glu167 · Cited by 86
“Among several indices validated to assess the risk of mortality, the Multidimensional Prognostic Index (MPI) has been found to be one of the most accurate (4,5).”
Background
Using the Multidimensional Prognostic Index to Predict Clinical Outcomes of Hospitalized Older Persons: A Prospective, Multicenter, International Study
Pilotto, A., Veronese, N., Daragjati, J., Cruz-Jentoft, A. J., Polidori, M. C., Mattace-Raso, F. U. S., Paccalin, M., Topinková, E., Siri, G., Greco, A., et al. (2018) · The Journals of Gerontology Series A · doi:10.1093/gerona/gly239 · Cited by 84
Primary Care Practitioners’ Views on Incorporating Long-term Prognosis in the Care of Older Adults
Schoenborn, N. L., Bowman, T. L., Cayea, D., Pollack, C. E., Feeser, S. A., & Boyd, C. M. (2016) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2016.0670 · Cited by 84
Systematic Review: Health‐Related Characteristics of Elderly Hospitalized Adults and Nursing Home Residents Associated with Short‐Term Mortality
Thomas, J. M., Cooney, L. M., & Fried, T. R. (2013) · Journal of the American Geriatrics Society · doi:10.1111/jgs.12273 · Cited by 82
Randomized Trial of Standard Adjuvant Chemotherapy Regimens Versus Capecitabine in Older Women With Early Breast Cancer: 10-Year Update of the CALGB 49907 Trial
Muss, H. B., Polley, M. C., Berry, D. A., Liu, H., Cirrincione, C., Theodoulou, M., Mauer, A. M., Kornblith, A. B., Partridge, A. H., Dressler, L. G., et al. (2019) · Journal of Clinical Oncology · doi:10.1200/jco.19.00647 · Cited by 81
Development and Validation of a 10-Year Mortality Prediction Model: Meta-Analysis of Individual Participant Data From Five Cohorts of Older Adults in Developed and Developing Countries
Suemoto, C. K., Ueda, P., Beltrán‐Sánchez, H., Lebrão, M. L., Duarte, Y. A. D. O., Wong, R., & Danaei, G. (2016) · The Journals of Gerontology Series A · doi:10.1093/gerona/glw166 · Cited by 76
“83 and less than 10% points difference between observed and predicted risk of mortality across deciles of risk (15).”
Influential
External validation of the Hospital-patient One-year Mortality Risk (HOMR) model for predicting death within 1 year after hospital admission
van Walraven, C., McAlister, F. A., Bakal, J. A., Hawken, S., & Donzé, J. D. (2015) · Canadian Medical Association Journal · doi:10.1503/cmaj.150209 · Cited by 76
Association Between Neighborhood Disadvantage and Functional Well-being in Community-Living Older Persons
Gill, T. M., Zang, E. X., Murphy, T. E., Leo-Summers, L. S., Gahbauer, E. A., Festa, N., Falvey, J. R., & Han, L. (2021) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2021.4260 · Cited by 73
Identification of a metabolic signature for multidimensional impairment and mortality risk in hospitalized older patients
Fontana, L., Addante, F., Copetti, M., Paroni, G., Fontana, A., Sancarlo, D., Pellegrini, F., Ferrucci, L., & Pilotto, A. (2013) · Aging Cell · doi:10.1111/acel.12068 · Cited by 72
“It is well known that MPI is a good predictor of short- and longterm mortality in older patients with a prognostic accuracy significantly higher than other prognostic tools (Pilotto et al., 2012; Yourman et al., 2012).”
BackgroundInfluential
Management of diabetes mellitus in older people with comorbidities
Huang, E. S. (2016) · BMJ · doi:10.1136/bmj.i2200 · Cited by 73
Prediction of early- and long-term mortality in adult patients acutely admitted to internal medicine: NRS-2002 and beyond
Sanson, G., Sadiraj, M., Barbin, I., Confezione, C., Matteis, D. D., Boscutti, G., Zaccari, M., & Zanetti, M. (2019) · Clinical Nutrition · doi:10.1016/j.clnu.2019.04.011 · Cited by 73
The Incidence and Cumulative Risk of Major Surgery in Older Persons in the United States
Becher, R. D., Wyk, B. V., Leo-Summers, L. S., Desai, M. M., & Gill, T. M. (2021) · Annals of Surgery · doi:10.1097/sla.0000000000005077 · Cited by 72
Predicting adverse drug reactions in older adults; a systematic review of the risk prediction models
Stevenson, J. M., Williams, J. L., Burnham, T. G., Prevost, A. T., Schiff, R., Erskine, S. D., & Davies, G. (2014) · Clinical Interventions in Aging · doi:10.2147/cia.s65475 · Cited by 72
Prevalence of aging population in the Middle East and its implications on cancer incidence and care
Hajjar, R. R., Atlı, T., Al-Mandhari, Z., Oudrhiri, M. Y., Balducci, L., & Silbermann, M. (2013) · Annals of Oncology · doi:10.1093/annonc/mdt268 · Cited by 73

Authors: Yourman, L. C., Lee, S. J., Schonberg, M. A., Widera, E. W., & Smith, A. K.
Affiliations: University of California, San Francisco (US)
San Francisco VA Medical Center (US)
Beth Israel Deaconess Medical Center (US)
Corresponding author: Smith, Alexander K.
ORCID: Yourman, Lindsey C.
Lee, Sei J.
Schonberg, Mara A.
Widera, Eric W.
Smith, Alexander K.
Venue: JAMA
Publisher: American Medical Association (AMA)
Published: 2012-01-11
Volume: 307
Issue: 2
Pages: 182
ISSN: 0002-9955 (ISSN-L)
0098-7484
DOI: 10.1001/jama.2011.1966
PMC: PMC3792853
OpenAlex: W2025056766
Cited by: 736
References: 74
Citations by year: 2026: 25 · 2025: 18 · 2024: 26 · 2023: 42 · 2022: 50 · 2021: 53 · 2020: 65 · 2019: 62 · 2018: 57 · 2017: 60 · 2016: 74 · 2015: 57 · 2014: 59 · 2013: 45 · 2012: 42
FWCI: 31.93
Type: journal article
Language: en
Open access: green
europepmc.org
Locations: JAMA (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
Funders: National Institute on Aging (K23AG040772, K23AG040779, T32AG000212)
National Center for Research Resources (UL1RR024131, KL2RR024130)
Topics: Health Sciences › Medicine › Geriatrics and Gerontology › Frailty in Older Adults
Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Palliative Care and End-of-Life Issues
Social Sciences › Demography › Insurance, Mortality, Demography, Risk Management
Keywords: prognostic score, mortality prediction, older adults, life expectancy, risk stratification, generalizability, transportability, index validation, concordance index, nursing homes, in-hospital mortality, community-dwelling older adults
MeSH terms: Aged, Aged, 80 and over, Decision Making, Patient Care, Humans, Life Expectancy, Middle Aged, Mortality, Predictive Value of Tests, Prognosis, Risk

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Prognostic Indices for Older Adults: A Systematic Review

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks