Abstract
Objective
Frailty state progression is common among older adults, so it is necessary to identify
predictors to implement individualized interventions. We aimed to develop and validate
a nomogram to predict frailty progression in community-living older adults.
Design
Prospective cohort study.
Setting and Participants
A total of 3170 Chinese community-living people aged ≥60 years were randomly assigned
to a training set or validation set at a ratio of 6:4.
Methods
Candidate predictors (demographic, lifestyle, and medical characteristics) were used
to predict frailty state progression as measured with the Fried frailty phenotype
at a 4-year follow-up, and multivariate logistic regression analysis was conducted
to develop a nomogram, which was validated internally with 1000 bootstrap resamples
and externally with the use of a validation set. The C index and calibration plot were used to assess discrimination and calibration of
the nomogram, respectively.
Results
After a follow-up period of 4 years, 64.1% (917/1430) of the participants in the robust
group and 26.0% (453/1740) in the prefrail group experienced frailty progression,
which included 9.1% and 21.0%, respectively, who progressed to frailty. Predictors
in the final nomogram were age, marital status, physical exercise, baseline frailty
state, and diabetes. Based on this nomogram, an online calculator was also developed
for easy use. The discriminative ability was good in the training set (C index = 0.861) and was validated using both the internal bootstrap method (C index = 0.861) and an external validation set (C index = 0.853). The calibration plots showed good agreement in both the training
and validation sets.
Conclusions and Implications
An easy-to-use nomogram was developed with good apparent performance using 5 readily
available variables to help physicians and public health practitioners to identify
older adults at high risk for frailty progression and implement medical interventions.
Keywords
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References
- Frailty: Implications for clinical practice and public health.Lancet. 2019; 394: 1365-1375
- Frailty and fracture, disability, and falls: A multiple country study from the global longitudinal study of osteoporosis in women.J Am Geriatr Soc. 2013; 61: 327-334
- Frailty as a predictor of disabilities among community-dwelling older people: A systematic review and meta-analysis.Disabil Rehabil. 2017; 39: 1897-1908
- Frailty as a predictor of short-term adverse outcomes.Peer J. 2015; 3: e1121
- Frailty index as a predictor of mortality: A systematic review and meta-analysis.Age Ageing. 2018; 47: 193-200
- Prevalence of frailty in community-dwelling older persons: A systematic review.J Am Geriatr Soc. 2012; 60: 1487-1492
- Frailty in older adults: Evidence for a phenotype.J Gerontol A Biol Sci Med Sci. 2001; 56: M146-M156
- Management of frailty: Opportunities, challenges, and future directions.Lancet. 2019; 394: 1376-1386
- Frailty syndrome: A transitional state in a dynamic process.Gerontology. 2009; 55: 539-549
- Transitions between frailty states among community-dwelling older people: A systematic review and meta-analysis.Ageing Res Rev. 2019; 50: 81-88
- Frailty state transitions and associated factors in South Australian older adults.Geriatr Gerontol Int. 2018; 18: 1549-1555
- Transitions in frailty status in older adults in relation to mobility: A multistate modeling approach employing a deficit count.J Am Geriatr Soc. 2011; 59: 524-529
- Factors influencing transitions between frailty states in elderly adults: The Progetto Veneto Anziani Longitudinal Study.J Am Geriatr Soc. 2017; 65: 179-184
- Frailty transitions in the San Antonio longitudinal study of aging.J Am Geriatr Soc. 2012; 60: 652-660
- Patterns and predictors of frailty transitions in older men: The osteoporotic fractures in men study.J Am Geriatr Soc. 2017; 65: 2473-2479
- Transitions in frailty states among community-living older adults and their associated factors.J Am Med Dir Assoc. 2014; 15: 281-286
- Risk factors of progression to frailty: Findings from the Singapore longitudinal ageing study.J Nutr Health Aging. 2020; 24: 98-106
- Frailty state among Indonesian elderly: Prevalence, associated factors, and frailty state transition.BMC Geriatr. 2019; 19: 182
- Is neighborhood green space associated with less frailty? Evidence from the Mr. and Ms. Os (Hong Kong) study.J Am Med Dir Assoc. 2018; 19: 528-534
- Nutritional and frailty state transitions in the Singapore longitudinal aging study.J Nutr Health Aging. 2018; 22: 1221-1227
- Prognosis and prognostic research: What, why, and how?.BMJ. 2009; 338: b375
- Clinical prediction rules.BMJ. 2012; 344: d8312
- Nomograms in oncology: More than meets the eye.Lancet Oncol. 2015; 16: e173-e180
- Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement.BMJ. 2015; 350: g7594
- Bayesian information criterion for longitudinal and clustered data.Stat Med. 2011; 30: 3050-3056
- How to build and interpret a nomogram for cancer prognosis.J Clin Oncol. 2008; 26: 1364-1370
- Discrimination and calibration of clinical prediction models: Users' guides to the medical literature.JAMA. 2017; 318: 1377-1384
- Overall C as a measure of discrimination in survival analysis: Model specific population value and confidence interval estimation.Stat Med. 2004; 23: 2109-2123
- Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.Stat Med. 1996; 15: 361-387
- Decision curve analysis.JAMA. 2015; 313: 409-410
- Multiple imputation: A flexible tool for handling missing data.JAMA. 2015; 314: 1966-1967
- Ignoring floor and ceiling effects may underestimate the effect of carotid artery stenting on cognitive performance.J Neurointerv Surg. 2016; 8: 747-751
- Marital status and risk of physical frailty: A systematic review and meta-analysis.J Am Med Dir Assoc. 2020; 21: 322-330
- Marital status and frailty in older people: Gender differences in the Progetto Veneto Anziani longitudinal study.J Womens Health (Larchmt). 2016; 25: 630-637
- Changes in frailty among community-dwelling Chinese older adults and its predictors: Evidence from a two-year longitudinal study.BMC Geriatr. 2020; 20: 130
- Benefits of moderate physical activity despite frailty.JAMA. 2018; 319: 1190
- Physical activity in older age: Perspectives for healthy ageing and frailty.Biogerontology. 2016; 17: 567-580
- Prospective association among diabetes diagnosis, HbA, glycemia, and frailty trajectories in an elderly population.Diabetes Care. 2019; 42: 1903-1911
- Regulation of amino acid and glucose transporters in endothelial and smooth muscle cells.Physiol Rev. 2003; 83: 183-252
- Frailty and the endocrine system.Lancet Diabetes Endocrinol. 2018; 6: 743-752
- Diabetes and frailty: Two converging conditions?.Can J Diabetes. 2016; 40: 77-83
- Frailty in elderly diabetes patients.Endocr J. 2018; 65: 1-11
References
- Notice on printing and distributing “the standard of health management Service of elderly in Shanghai”: [2018] No. 002. [2018-01-25].(Available at:)http://wsjkw.sh.gov.cn/jcws2/20180815/0012-58126.htmlDate accessed: February 9, 2021
- The Lawton instrumental activities of daily living (IADL) scale.Am J Nurs. 2008; 108: 52-62
- Frailty in older adults: Evidence for a phenotype.J Gerontol A Biol Sci Med Sci. 2001; 56: M146-M156
- Physical activity questionnaires for adults: A systematic review of measurement properties.Sports Med. 2010; 40: 565-600
Article info
Publication history
Published online: June 12, 2021
Footnotes
This work was supported by the Youth Program of Zhongshan Hospital of Fudan University (grant no. 076).
The authors declare no conflicts of interest.
Identification
Copyright
© 2021 AMDA - The Society for Post-Acute and Long-Term Care Medicine.
