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The landscape of prostate cancer research in Canada.

2023· article· en· W4324137081 on OpenAlexfundaboutno aff
Mike Fraser, Atiqa Mohammad

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsnot available
FundersMovember Canada
KeywordsMedicineProstate cancerInvestment (military)CancerCancer registryDiseaseFamily medicineDatabaseGerontologyPolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

394 Background: Prostate cancer (PCa) is the most prevalent malignancy in Canadian men; in 2023, an estimated 24,700 men will be diagnosed while ~4,700 will die of their disease. Lifetime risk of developing PCa is approximately 1-in-8 and approximately 3% of all deaths of Canadian men are caused by the disease. While Canada has a robust, modern health research landscape, with major academic centres located in all provinces and territories, the investment in academic PCa research – and the impact of that investment – has not been systematically quantified. An improved understanding of this landscape is necessary to ensure research funding remains efficient, impactful, and equitable. As such, we evaluated the size, scope, and impact of the investment in academic PCa research in Canada. Methods: We extracted funding records from the Canadian Research Information System (CRIS), the United States Congressionally Directed Medical Research Program database and the United States National Institutes of Health RePORT database for the National Cancer Institute, using keywords ‘prostate’ OR ‘prostatic’ AND ‘cancer’ OR ‘carcinoma’ for 1999-2021. US-sourced records were included when the principal investigator (PI) was based at a Canadian institution at the time the award was granted. Records were validated using data from the Canadian Cancer Research Alliance (CCRA). Intramural and industry-derived funding was unavailable and thus excluded from the analysis. Results: We identified 1,748 unique funding events (FEs) from 33 sources. These FEs involved 1,561 investigators and had an inflation-adjusted value of $682,113,116. The top three funders of PCa research were the Canadian Institutes of Health Research, Movember Canada, and the Canadian Cancer Society. Basic and translational research received ~83% of all funding while psychosocial, health economics, and epidemiology research received only ~7.2%. Strikingly, we found that 30.5% of all funding was held by 1% of investigators. We identified 6,671 dyads ( ie. pairs of collaborating investigators); 85% collaborated only once, while 15% collaborated at least twice (range: 2-19). Female investigators participated in significantly fewer collaborations than males (P: 3.28 x 10-3) and were less likely than expected to serve as PI (P: 8.87 x 10-8). FEs with ≥ one female PI had a significantly lower value than those with only male PIs (P: 1.34 x 10-6) and FEs with only female PIs had a significantly value than those with only male PIs (P: 7.32 x 10-4). Conclusions: While Canadian PCa research has been highly funded over the past 25 years, there remain substantial funding disparities across scientific disciplines, geographic regions, and, in particular, gender. There is also substantial ‘wealth inequality’; a small minority of investigators receive most of the funding. We are currently assessing stakeholder attitudes toward these disparities, to help inform the next phase of PCa research funding in Canada.

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)0.012
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.944

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.038
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0160.048
Science and technology studies0.0080.002
Scholarly communication0.0080.001
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.636
GPT teacher head0.682
Teacher spread0.046 · 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.

Study designObservational
DomainEvaluation
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".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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