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Record W4411211637 · doi:10.6004/jnccn.2025.7020

Telehealth Geriatric Assessment and Supportive Care Intervention (GAIN-S) Program: A Randomized Clinical Trial

2025· article· en· W4411211637 on OpenAlex
Cristiane Decat Bergerot, Paulo Gustavo Bergerot, Marianne Razavi, Marcos Vinicius da Silva França, Jose Adolfo Cerveira, William Hiromi Fuzita, Andressa Cardoso de Azeredo, Gabriel Marques dos Anjos, Vitor Fiorin de Vasconcellos, Errol J. Philip, João Nunes de Matos Neto, Jorge Canedo, Mariana Tosello Laloni, Carlos Gil Ferreira, Marco Murilo Buso, Sumanta K. Pal, Ryan David Nipp, Areej El‐Jawahri, Enrique Soto-Perez-de-Celis, William Dale

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of the National Comprehensive Cancer Network · 2025
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTelehealthRandomized controlled trialIntervention (counseling)Clinical trialPhysical therapyMEDLINETelemedicineNursingHealth careInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Older patients with cancer face challenges in accessing high-quality cancer care, especially in resource-limited settings. We assessed the impact of a telehealth-adapted Geriatric Assessment-Guided Intervention (GAIN-S) among older Brazilians with metastatic cancer. PATIENT AND METHODS: This randomized clinical trial enrolled adults aged ≥65 years with metastatic cancer between June 2022 and July 2023. Patients were randomly assigned (1:1) to receive either usual care or GAIN-S. In the GAIN-S arm, a multidisciplinary team (MDT) developed an intervention plan based on impairments identified through geriatric assessment (GA). The plan included MDT discussions and targeted referrals to psychiatry, social services, nutrition, supportive care, and certified fitness training over a 3-month period. Assessments were conducted at baseline and at 3 months. The primary outcome was change in physical function, measured by instrumental activities of daily living (IADL) at 3 months. Secondary endpoints included changes in mood (assessed using the Geriatric Depression Scale [GDS]), quality of life (assessed using the Functional Assessment of Cancer Therapy-General [FACT-G]), and prognostic understanding. T tests and linear mixed models were used to compare groups at each timepoint and to assess longitudinal change. RESULTS: A total of 80 patients were enrolled (40 per arm). Clinical characteristics were well balanced between arms. Most patients were female (55.8%), with a mean age of 74 years (range, 65-88). At 3 months, patients in the GAIN-S arm showed improvements in physical function (IADL, +1.8), mood (GDS, -2.7), quality of life (FACT-G, +13.2), and symptom burden (assessed using the Edmonton Symptom Assessment System [ESAS], -14.6), all with P values <.001. Patients in the intervention group also demonstrated more accurate prognostic understanding (P<.01). CONCLUSIONS: This study demonstrates the efficacy of the telehealth-administered GAIN-S intervention in older adults with cancer in Brazil. These findings underscore the importance of tailoring GA-guided interventions for resource-limited settings.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.465
Teacher spread0.407 · 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