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Testosterone recovery following androgen suppression and prostate radiotherapy (TRANSPORT): Updated individual patient data meta-analyses from the MARCAP consortium.

2023· article· en· W4379282240 on OpenAlexaffabout
Wee Loon Ong, Holly Wilhalme, Jeremy Millar, Allison Steigler, James W. Denham, David Joseph, Soumyajit Roy, Shawn Malone, Nicholas G. Nickols, Matthew B. Rettig, Luca Valle, Michael L. Steinberg, Yilun Sun, Nicholas G. Zaorsky, Daniel E. Spratt, Luís Souhami, Nathalie Carrier, Abdenour Nabid, Amar U. Kishan

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeSunnybrook Health Science CentreMcGill University Health CentreUniversity of OttawaOttawa HospitalHealth Sciences Centre
Fundersnot available
KeywordsMedicineProstate cancerTestosterone (patch)Androgen deprivation therapyAndrogenRandomized controlled trialRadiation therapyUrologyProstateInternal medicineCancerHormone

Abstract

fetched live from OpenAlex

5096 Background: Time to testosterone recovery (TR) following androgen deprivation therapy (ADT) and radiotherapy for prostate cancer varies following cessation of ADT. We aimed to quantify the association between time to TR and duration of ADT and patient age. Methods: We identified prospective randomized trials of prostate radiotherapy and ADT in the Meta-Analysis of Randomized trials in Cancer of the Prostate (MARCAP) consortium for which prospectively collected serial testosterone values were available. The time to non-castrate TR (NCTR) (>1.7ng/mL), non-hypogonadal TR (NHTR) (>8.0ng/mL) and full TR (FTR) (>10.5ng/mL) were estimated from the end date of prescribed ADT using the Kaplan Meier method. Cox regression was used to evaluate the differences in time to TR for men aged <65 years and ≥65 years for each duration of ADT. Interaction effects between ADT duration and patient age on TR were evaluated. Results: 2628 men from 5 trials (TROG 9601, TROG 0304, PCSIII, PCSIV, and Ottawa-01) met the inclusion criteria for analysis. Of these, 236, 1485, 731, and 176 men had 3-, 6-, 18-, and 36-months of ADT respectively. 1502 (57%) men had baseline (pre-ADT) testosterone data available, of which 99% (1494/1502) had non-castrate testosterone (>1.7ng/mL), and 78% (1178/1502) had normal testosterone (>10.5ng/mL) at baseline. At last follow-up, there were 96% (2522/2628), 77% (2035/2628) and 65% (1700/2628) of men who had NCTR, NHTR and FTR respectively. The median time (range) to NCTR was 1.9 (0.2-60), 6.2 (0.0-92), 6.3 (0.0-92), and 15.7 (0.1-75) months for men who had 3-, 6-, 18- and 36-months of ADT, respectively. The median time (range) to NHTR was 2.5 (0.4-73), 11.2 (0.1-93), 17.7 (0.2-92), and 53.4 (5.3-76) months for men who had 3-, 6-, 18- and 36-months of ADT, respectively. The median time (range) to FTR was 5.8 (0.4-72), 16.7 (0.3-95), and 26.0 (0.2-90) for men who had 3-, 6-, and 18-months of ADT, respectively, while the median time to FTR was not reached in men who had 36-months of ADT. In men who had 6-months of ADT, men aged ≥65 years were 35% (95%CI=26-43%) less likely to have FTR compared to men aged <65 years, while for those who had 18-months of ADT, men aged ≥ 65 years were 52% (95%CI=41-60%) less likely to have FTR compared to men aged < 65 years. There was no statistically significant interaction between the effect of ADT duration and age on the time to FTR (interaction P=0.07 for the entire cohort). Conclusions: In this updated individual patient-data meta-analysis of prospectively collected serial testosterone data from 5 randomized trials, substantial delay in FTR in men who had longer duration of ADT was observed, consistent with prior analyses. Approximately 1-in-3 men did not have FTR, which may have life-long impacts on their quality of life.

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)0.020
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.038
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.039
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.434
GPT teacher head0.527
Teacher spread0.094 · 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 designMeta-analysis
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
Published2023
Admission routes2
Has abstractyes

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