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Record W4282974773 · doi:10.1111/jgs.17929

Geriatrics assessment in older adults referred for hematopoietic cell transplantation

2022· letter· en· W4282974773 on OpenAlexaboutno aff
Philip H. Sossenheimer, Sushma Bharadwaj, Laura Johnston, Vyjeyanthi S. Periyakoil

Bibliographic record

VenueJournal of the American Geriatrics Society · 2022
Typeletter
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute on Aging
KeywordsMedicineTransplantationHematopoietic cellReferralPopulationGeriatricsHematopoietic stem cell transplantationGerontologyAdverse effectPediatricsInternal medicineStem cellFamily medicineHaematopoiesisPsychiatry

Abstract

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Hematopoietic cell transplantation (HCT) is an indicated therapy for several hematologic diseases common in older adults. The average age at HCT is increasing, with 26% of allogeneic transplant recipients in 2019 being older than 65, compared with 9% in 2009. While older transplant patients benefit from the positive outcomes of HCT,1-3 they are at risk of increased morbidity and mortality4-6 due to multiple factors including multimorbidity, frailty and functional decline. As HCT becomes more prevalent among older adults, geriatricians and oncologists must collaborate to best identify patients will benefit most from HCT. Geriatric assessment (GA) is a multidimensional assessment designed to evaluate an older person's physical health, cognition, mental health, functional status, and socioenvironmental circumstances. Recent data shows GA improved outcomes in the general population,7-10 and that pre-transplant GA improves outcomes among patients undergoing HCT.5 It is not clear, however, whether routine pre-transplant GA can help in selecting patients who will most benefit from HCT while minimizing adverse outcomes. Our study investigates the feasibility of incorporating a baseline GA at the time of the initial evaluation for allogeneic transplant at our bone marrow transplant (BMT) program. We hypothesized that patients with lower scores on a GA at the time of referral to our BMT program would be less likely to undergo HCT and would have worse outcomes if they did undergo HCT. Between November 2018 and July 2020, 54 patients ≥60 years of age referred to Stanford for allogeneic HCT underwent a GA during their initial pre-transplant appointment. In this context, the term GA refers to the evaluation by an individual geriatrician (VSP) in conjunction with trained medical assistants (MA). The GA consisted of the Montreal Cognitive Assessment (MOCA), Vulnerable Elders Survey (VES-13), Patient-Reported Outcomes Measurement Information System (PROMIS), and the timed up and go (TUG). Assessments were only performed if there was a trained MA available in clinic on a given day. Results of the GA were not shared with the medical team or used to inform treatment decisions. Patients who underwent HCT were followed prospectively via the Stanford BMT Database. All other data were collected retrospectively through chart review using the Stanford Research Repository. Our primary outcome was undergoing HCT, and secondary outcome was mortality. Continuous variables were compared using t test (parametric) or Mann–Whitney U (nonparametric) test. Categorical variables were compared using the Fisher's exact test. This study was approved by the Stanford IRB. Fifty-four patients underwent a GA at their initial pre-transplant appointment, which took an average 20 min to complete. Seventeen of the 54 patients underwent HCT. The median age of the cohort was 71 (IQR 62–77) and was not significantly different between groups (69.6 vs 70.3, p = 0.6). There was no association between any GA element and subsequent HCT (Figure 1). The 1-year mortality was 53% (9/17) for those patients who received HCT and 27% (10/37) for those who did not receive HCT (p = 0.22, NS). The primary cause of death among patients who underwent HCT was relapse of their malignancy (4), followed by acute graft versus host disease (2). Among patients who did not undergo HCT, the primary cause of death was infection (4). The baseline Global Physical Health Score was associated with mortality, with patients with higher scores more likely to die by 1 year (median 10 vs 15, p = 0.04). The sample size was too small for further subgroup analyses. No other element of the GA was associated with 1-year mortality. As more older adults are considered for HCT, incorporation of a GA to identify coexisting health conditions and functional disability will become increasingly important. This is the first study we are aware of that demonstrates the feasibility of screening patients at the time of HCT evaluation. In this study, we specifically blinded the care team to the to the results of the patients' baseline GA and found that these important markers of overall health and functional status were no different between patients who were selected for transplant and those who were not. Since elements of the GA have been associated with both overall and progression free survival,11, 12 our result highlights an opportunity for the routine use of GA prior to HCT to help select candidates who may experience better outcomes after transplant. In addition, it underscores the geriatrician's role in co-managing patients undergoing HCT: To assist with the implementation and interpretation of routine GA, to intervene on issues that are identified during GA, and to assist in treating age-related complications that arise. This will require further research, including observational studies that incorporate GA assessment results over time to determine the impact of HCT treatments on the recipients' GA scores and randomized clinical trials that randomize whether the baseline GA score is provided to the clinical team to assess the impact this information may have on clinical decision-making and patient mortality and morbidity. Overall, our study highlights both the challenges and opportunities in incorporating a GA as a routine part of the baseline assessment and suggests a role for interdisciplinary management of all older adults undergoing HCT. Dr. Periyakoil and Dr. Johnston contributed to the conception and design of this project, analysis and interpretation of data, and revision of the article. Dr. Sossenheimer contributed to the analysis and interpretation of data, and drafting and revision of the article. Dr. Bharadwaj contributed to the analysis and interpretation of data, and revision of the article. All authors approved the final version for publication. All authors meet the criteria for authorship stated in the Uniform Requirements for Manuscripts Submitted to Biomedical Journals. Dr. Periyakoil's time is funded by the following grants: P30 AG059307/AG/NIA NIH HHS/United States; R01 AG062239/ AG/NIA NIH HHS/United States; U54 MD010724/MD/ NIMHD NIH HHS/United States. Drs. Sossenheimer, Bhadarwaj, and Johnston have no conflicts of interest to disclose. There was no sponsor for this study. This project was supported by a grant from the Stanford Cancer Center Clinical Innovation Fund.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.285
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2022
Admission routes1
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