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Remote symptom monitoring (RSM) during treatment for metastatic prostate cancer (mPC) in older men: Feasibility and efficacy.

2022· article· en· W4286296056 on OpenAlexafffundabout
Shabbir M.H. Alibhai, Henriette Breunis, Narhari Timilshina, Gregory Feng, Milothy Parthipan, Abirami Sudharshan, Aaron R. Hansen, Antonio Finelli, Padraig Warde, George Tomlinson, Monika K. Krzyzanowska, Andrew Matthew, Hance Clarke, Daniel Santa Mina, Enrique Soto‐Pérez‐de‐Celis, Martine Puts, Urban Emmenegger

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
FundersProstate Cancer Canada
KeywordsMedicineProstate cancerQuality of life (healthcare)CohortMoodAnxietyProspective cohort studyCohort studyPhysical therapyPsychological interventionInternal medicineCancerPsychiatry

Abstract

fetched live from OpenAlex

12056 Background: Emerging data support multiple benefits of RSM during chemotherapy to improve outcomes. These studies do not focus on older adults and do not include non-chemotherapy strategies. mPC represents a major burden in older men. Although both chemotherapy and androgen receptor axis-targeted therapies (ARATs) prolong survival, toxicities are substantial and increased in older men. Understanding the feasibility of RSM and key symptoms experienced by men with mPC on treatment is crucial to designing appropriate supportive care interventions. We aimed to assess RSM feasibility and understand key symptoms during treatment with chemotherapy or an ARAT among older men. Methods: Older adults aged 65+ starting chemotherapy, an ARAT, or Radium-223 for mPC were enrolled in a prospective observational multicentre study. Participants completed the Edmonton Symptom Assessment Scale (ESAS) on weekdays online or by phone. Weekly detailed questionnaires assessed mood, anxiety, fatigue, insomnia, and pain. Notifications were sent to the clinical oncology team with severe symptoms (ESAS 7 or higher). Study duration was the first treatment cycle (̃3-4 weeks). Feasibility data were analyzed descriptively. Linear mixed effects models examined symptoms over time and by cohort. Clinician responses were assessed descriptively. Results: A total of 90 men were included (mean age 76.5y, 48% ARAT, 38% chemotherapy, and 14% Radium-223, 42% frail by Vulnerable Elders Survey-13 cutoff of 3+). Approximately half the patients preferred phone-based RSM. Patients provided RSM responses in 1,874 of approximately 2,000 (94%) instances. In the combined cohort, the most common symptoms of moderate to severe intensity (ESAS 4 or higher) occurring at least once were poor well-being (66%), fatigue (62%), reduced appetite (56%), insomnia (54%), and pain (46%). Symptom patterns were similar between chemotherapy and ARAT groups. Moderate to severe symptoms were more common and lasted longer among frail than non-frail men. Symptoms tended to remain stable or improve over the course of 3-4 weeks of RSM. 89% of participants were satisfied or very satisfied with RSM, although daily reporting was reported by several as burdensome. 45% had severe symptoms from RSM leading to informing the oncology care team, 79% of whom were followed up by a nurse or physician, and 12% of treatments were modified. Conclusions: RSM is feasible, acceptable to older adults, and identifies clinically relevant symptoms, but accommodation needs to be made for phone and the optimal frequency of RSM needs to be established. Poor well-being, fatigue, reduced appetite, and insomnia occurred in over half of participants. Longer-term follow up will be important.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.221
GPT teacher head0.543
Teacher spread0.322 · 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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Citations1
Published2022
Admission routes3
Has abstractyes

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