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Record W4210439766 · doi:10.2196/preprints.12579

Comprehensive Lifestyle Improvement Program for Prostate Cancer (CLIPP): Protocol for a Feasibility and Exploratory Efficacy Study in Men on Androgen Deprivation Therapy (Preprint)

2018· preprint· en· W4210439766 on OpenAlexaff
Amit M. Algotar, Chiu‐Hsieh Hsu, H.‐H. Sherry Chow, Shona T. Dougherty, Hani M. Babiker, David G. Marrero, Ivo Abraham, Rachit Kumar, Jennifer A. Ligibel, Kerry S. Courneya, Cynthia A. Thomson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAndrogen deprivation therapyMedicineProstate cancerPhysical therapyPsychological interventionCancerOncologyInternal medicineGerontologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND Androgen deprivation therapy (ADT) for prostate cancer is associated with adverse cardiometabolic effects such as reduced libido, hot flashes, metabolic syndrome, diabetes, myocardial infarction, and stroke. This reduces quality of life and potentially increases mortality. Several large clinical trials have demonstrated improvements in cardiometabolic risk with comprehensive multimodality lifestyle modification. However, there is a lack of data for such interventions in men on ADT for prostate cancer, and existing studies have used non-standardized interventions or lacked data on metabolic risk factors. OBJECTIVE The Comprehensive Lifestyle Improvement Project for Prostate Cancer (CLIPP) is designed to address these gaps by using an intervention modeled on the Diabetes Prevention Program, a standardized multicomponent intervention with demonstrated effectiveness in reducing cardiometabolic risk factors that has been successfully adapted for multiple disease types including breast cancer. METHODS A single-arm unblinded clinical trial will be conducted to determine the feasibility of conducting a 24-week comprehensive lifestyle modification intervention that targets weight loss and increased physical activity modeled on the Diabetes Prevention Program in 30 men on ADT for prostate cancer. Secondary aims are to determine the effect of the intervention on cardiometabolic markers and quality of life. The tertiary aim is to determine the effect of the intervention on markers of inflammation and angiogenesis, important mechanisms for prostate cancer progression. Participants will be recruited from the University of Arizona Cancer Center and the surrounding community. The intervention will be delivered weekly in person and over the phone for 16 weeks. For Weeks 16-24, participants receive weekly phone calls from the study health coach to motivate them to continue their lifestyle modification. Questionnaire and biological data are collected at baseline, 12 weeks, and 24 weeks. Body composition using dual-energy x-ray absorptiometry scans will be performed at baseline and end of study. RESULTS Based on a sample size of 30, the two-sided 95% confidence interval will not be wider than 0.373 standard deviations for the adherence rate and will not be wider than 0.374 for the retention rate. In addition, the study will have a power of 80% to detect a change of 0.47 standard deviations from baseline for each of the markers investigated in the secondary and tertiary aims assuming a within-subject correlation of 0.20 at a significance level of 5%. The recruitment period is from October 2018 to April 2019. CONCLUSIONS The aim of CLIPP is to determine the feasibility of conducting a Diabetes Prevention Program–style comprehensive lifestyle modification intervention in men with ADT for prostate cancer and its effects on cardiometabolic adverse effects, quality of life, as well as markers of inflammation and angiogenesis. Results will inform the development of future clinical trials in this population. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/12579

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)0.026
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.050
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.016
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0020.003
Science and technology studies0.0040.003
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0500.013

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 head0.117
GPT teacher head0.434
Teacher spread0.317 · 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 designNon-randomized trial
Domainnot available
GenreProtocol

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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