@article {12231, title = {Incidence of potentially disruptive medical and social events in older adults with and without dementia.}, journal = {Journal of the American Geriatrics Society}, volume = {70}, year = {2022}, pages = {1461-1470}, abstract = {

BACKGROUND: Potentially disruptive medical, surgical, and social events-such as pneumonia, hip fracture, and widowhood-may accelerate the trajectory of decline and impact caregiving needs in older adults, especially among people with dementia (PWD). Prior research has focused primarily on nursing home residents with dementia. We sought to assess the incidence of potentially disruptive events in community-dwelling people with and without dementia.

METHODS: Retrospective cohort study of participants aged 65+ enrolled in the Health and Retirement Study between 2010 and 2018 (n~=~9346), including a subset who were married-partnered at baseline (n~=~5105). Dementia was defined with a previously validated algorithm. We calculated age-adjusted and gender-stratified incidence per 1000 person-years and incidence rate ratios of: 1) hospitalization for pneumonia, 2) hip fracture, and 3) widowhood in people with and without dementia.

RESULTS: PWD (n~=~596) were older (mean age 84 vs. 75) and a higher proportion were female (67\% vs. 57\%) than people without dementia (PWoD) (n~=~8750). Age-adjusted incidence rates (per 1000 person-years) of pneumonia were higher in PWD (113.1; 95\% CI 94.3, 131.9) compared to PWoD (62.1; 95\% CI 54.7, 69.5), as were hip fractures (12.3; 95\% CI 9.1, 15.6 for PWD compared to 8.1; 95\% CI 6.9, 9.2 in PWoD). Point estimates of widowhood incidence were slightly higher for PWD (25.3; 95\% CI 20.1, 30.5) compared to PWoD (21.9; 95\% CI 20.3, 23.5), but differences were not statistically significant. The association of dementia with hip fracture-but not pneumonia or widowhood-was modified by gender (male incidence rate ratio [IRR] 2.24, 95\% CI 1.34, 3.75 versus female IRR 1.31 95\% CI 0.92,1.86); interaction term p~=~0.02).

CONCLUSIONS: Compared to PWoD, community-dwelling PWD had higher rates of pneumonia and hip fracture, but not widowhood. Knowing how often PWD experience these events can aid in anticipatory guidance and care planning for this growing population.

}, keywords = {Dementia, Hip fracture, Pneumonia, Widowhood}, issn = {1532-5415}, doi = {10.1111/jgs.17682}, author = {Hunt, Lauren J and R Sean Morrison and Gan, Siqi and Espejo, Edie and Katherine A Ornstein and W John Boscardin and Smith, Alexander K} } @article {11579, title = {A Novel Method for Identifying a Parsimonious and Accurate Predictive Model for Multiple Clinical Outcomes.}, journal = {Computer Methods and Programs in Biomedicine}, volume = {204}, year = {2021}, pages = {106073}, abstract = {

BACKGROUND AND OBJECTIVE: Most methods for developing clinical prognostic models focus on identifying parsimonious and accurate models to predict a single outcome; however, patients and providers often want to predict multiple outcomes simultaneously. As an example, for older adults one is often interested in predicting nursing home admission as well as mortality. We propose and evaluate a novel predictor-selection computing method for multiple outcomes and provide the code for its implementation.

METHODS: Our proposed algorithm selected the best subset of common predictors based on the minimum average normalized Bayesian Information Criterion (BIC) across outcomes: the Best Average BIC (baBIC) method. We compared the predictive accuracy (Harrell{\textquoteright}s C-statistic) and parsimony (number of predictors) of the model obtained using the baBIC method with: 1) a subset of common predictors obtained from the union of optimal models for each outcome (Union method), 2) a subset obtained from the intersection of optimal models for each outcome (Intersection method), and 3) a model with no variable selection (Full method). We used a case-study data from the Health and Retirement Study (HRS) to demonstrate our method and conducted a simulation study to investigate performance.

RESULTS: In the case-study data and simulations, the average Harrell{\textquoteright}s C-statistics across outcomes of the models obtained with the baBIC and Union methods were comparable. Despite the similar discrimination, the baBIC method produced more parsimonious models than the Union method. In contrast, the models selected with the Intersection method were the most parsimonious, but with worst predictive accuracy, and the opposite was true in the Full method. In the simulations, the baBIC method performed well by identifying many of the predictors selected in the baBIC model of the case-study data most of the time and excluding those not selected in the majority of the simulations.

CONCLUSIONS: Our method identified a common subset of variables to predict multiple clinical outcomes with superior balance between parsimony and predictive accuracy to current methods.

}, keywords = {backward elimination, Bayesian Information Criterion, prognostic models, Survival Analysis, variable selection}, issn = {1872-7565}, doi = {10.1016/j.cmpb.2021.106073}, author = {L Grisell Diaz-Ramirez and Lee, Sei J and Alexander K Smith and Gan, Siqi and W John Boscardin} } @article {11523, title = {A Novel Metric for Developing Easy-to-Use and Accurate Clinical Prediction Models: The Time-cost Information Criterion.}, journal = {Medical Care}, volume = {59}, year = {2021}, pages = {418-424}, abstract = {

BACKGROUND: Guidelines recommend that clinicians use clinical prediction models to estimate future risk to guide decisions. For example, predicted fracture risk is a major factor in the decision to initiate bisphosphonate medications. However, current methods for developing prediction models often lead to models that are accurate but difficult to use in clinical settings.

OBJECTIVE: The objective of this study was to develop and test whether a new metric that explicitly balances model accuracy with clinical usability leads to accurate, easier-to-use prediction models.

METHODS: We propose a new metric called the Time-cost Information Criterion (TCIC) that will penalize potential predictor variables that take a long time to obtain in clinical settings. To demonstrate how the TCIC can be used to develop models that are easier-to-use in clinical settings, we use data from the 2000 wave of the Health and Retirement Study (n=6311) to develop and compare time to mortality prediction models using a traditional metric (Bayesian Information Criterion or BIC) and the TCIC.

RESULTS: We found that the TCIC models utilized predictors that could be obtained more quickly than BIC models while achieving similar discrimination. For example, the TCIC identified a 7-predictor model with a total time-cost of 44 seconds, while the BIC identified a 7-predictor model with a time-cost of 119 seconds. The Harrell C-statistic of the TCIC and BIC 7-predictor models did not differ (0.7065 vs. 0.7088, P=0.11).

CONCLUSION: Accounting for the time-costs of potential predictor variables through the use of the TCIC led to the development of an easier-to-use mortality prediction model with similar discrimination.

}, keywords = {Bayesian Information Criterion, Methodology}, issn = {1537-1948}, doi = {10.1097/MLR.0000000000001510}, author = {Lee, Sei J and Alexander K Smith and Ramirez-Diaz, Ledif G and Kenneth E Covinsky and Gan, Siqi and Chen, Catherine L and W John Boscardin} } @article {11657, title = {Pre-existing geriatric conditions in older adults with poor prognosis cancers.}, journal = {Journal of Clinical Oncology}, volume = {39}, year = {2021}, pages = {12044-12044}, abstract = {Background: Older adults with poor prognosis cancers are more likely to experience toxicity from cancer-directed therapies. Although geriatric assessment (GA) reduces chemotherapy toxicity by detecting pre-existing conditions, GA can be difficult for oncologists to perform because of limited time and resources. We aim to determine the prevalence of pre-existing geriatric conditions that could be detected if GA were performed during routine oncology care. Methods: We used the Health and Retirement Study (HRS) linked with Medicare (1998-2016) to identify adults age >65 with poor prognosis cancers (median overall survival < 1 year). The HRS is a biennial nationally representative survey that asks about pre-existing geriatric conditions. Using the interview prior to the cancer diagnosis, we determined the presence of conditions included in GA: functional status (i.e. difficulty with climbing stairs, walking one block, getting up from a chair, bathing or showering, taking medications, and managing money), falls and injurious falls, unintentional weight loss, self-rated health, social support, mentation, advanced care planning, use of pain or sleep medications, and mobility. To identify groups with the highest prevalence of pre-existing geriatric conditions, we stratified results by age (adjusted for gender) and gender (adjusted for age). Results: Our study included 2,121 participants. At the time of cancer diagnosis, mean age was 76, 51\% were female, 79\% were non-Hispanic White, 26\% had lung cancer, 14\% had a GI cancer, and 60\% had other metastatic cancers. Mean time between the HRS interview and cancer diagnosis was 12.7 months. The median overall survival of the entire cohort was 9.6 months with a 45\% 1-year survival rate. The adjusted prevalence of pre-existing geriatric concerns were as follows: 65\% had difficulty with climbing several flights of stairs, 27\% had difficulty with walking one block, 47\% had difficulty getting up from a chair after sitting down, 12\% had difficulty in bathing or showering, 6\% had difficulty taking medications, 11\% had difficulty in managing money, 35\% had a fall in the last 2 years with 12\% of participants reporting injury after their fall. Those who were aged 85+, vs those aged 65-74, had higher rates of conditions indicative of cognitive impairment (e.g. 12 vs 4\% had difficulty taking medications, p = 0.000, 26\% vs 6\% had difficulty managing money, p = 0.000) and physical impairments (e.g. 54\% vs 30\% had falls, respectively, p = 0.000). Rates of geriatric conditions indicative of physical impairment were higher in women vs men (e.g. 72\% vs 58\% had difficulty climbing stairs, p = 0.000 and 52\% vs 41\% had difficulty getting up from a chair, p = 0.000). Conclusions: Patients with poor prognosis cancers have high rates of pre-existing geriatric conditions that can be detected by GA. Geriatric assessments could find important impairments that could be addressed prior to cancer therapy to reduce adverse effects.12044Background: Older adults with poor prognosis cancers are more likely to experience toxicity from cancer-directed therapies. Although geriatric assessment (GA) reduces chemotherapy toxicity by detecting pre-existing conditions, GA can be difficult for oncologists to perform because of limited time and resources. We aim to determine the prevalence of pre-existing geriatric conditions that could be detected if GA were performed during routine oncology care. Methods: We used the Health and Retirement Study (HRS) linked with Medicare (1998-2016) to identify adults age >65 with poor prognosis cancers (median overall survival < 1 year). The HRS is a biennial nationally representative survey that asks about pre-existing geriatric conditions. Using the interview prior to the cancer diagnosis, we determined the presence of conditions included in GA: functional status (i.e. difficulty with climbing stairs, walking one block, getting up from a chair, bathing or showering, taking medications, and managing money), falls and injurious falls, unintentional weight loss, self-rated health, social support, mentation, advanced care planning, use of pain or sleep medications, and mobility. To identify groups with the highest prevalence of pre-existing geriatric conditions, we stratified results by age (adjusted for gender) and gender (adjusted for age). Results: Our study included 2,121 participants. At the time of cancer diagnosis, mean age was 76, 51\% were female, 79\% were non-Hispanic White, 26\% had lung cancer, 14\% had a GI cancer, and 60\% had other metastatic cancers. Mean time between the HRS interview and cancer diagnosis was 12.7 months. The median overall survival of the entire cohort was 9.6 months with a 45\% 1-year survival rate. The adjusted prevalence of pre-existing geriatric concerns were as follows: 65\% had difficulty with climbing several flights of stairs, 27\% had difficulty with walking one block, 47\% had difficulty getting up from a chair after sitting down, 12\% had difficulty in bathing or showering, 6\% had difficulty taking medications, 11\% had difficulty in managing money, 35\% had a fall in the last 2 years with 12\% of participants reporting injury after their fall. Those who were aged 85+, vs those aged 65-74, had higher rates of conditions indicative of cognitive impairment (e.g. 12 vs 4\% had difficulty taking medications, p = 0.000, 26\% vs 6\% had difficulty managing money, p = 0.000) and physical impairments (e.g. 54\% vs 30\% had falls, respectively, p = 0.000). Rates of geriatric conditions indicative of physical impairment were higher in women vs men (e.g. 72\% vs 58\% had difficulty climbing stairs, p = 0.000 and 52\% vs 41\% had difficulty getting up from a chair, p = 0.000). Conclusions: Patients with poor prognosis cancers have high rates of pre-existing geriatric conditions that can be detected by GA. Geriatric assessments could find important impairments that could be addressed prior to cancer therapy to reduce adverse effects.}, keywords = {Cancer, Geriatric Assessment, Medicare, Pre-existing Conditions}, isbn = {0732-183X}, doi = {10.1200/JCO.2021.39.15_suppl.12044}, author = {Tsang, Mazie and Gan, Siqi and Wong, Melisa L. and Louise C Walter and Alexander K Smith} }