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Record W1512031039 · doi:10.1016/j.eururo.2015.05.046

Prostate Cancer Registries: Current Status and Future Directions

2015· review· en· W1512031039 on OpenAlexaff
Giorgio Gandaglia, Freddie Bray, Matthew R. Cooperberg, R. Jeffrey Karnes, Michael Leveridge, Kim Moretti, Declan G. Murphy, David F. Penson, David C. Miller

Bibliographic record

VenueEuropean Urology · 2015
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsQueen's University
FundersWorld Health Organization
KeywordsMedicineProstate cancerMEDLINEPopulationDiseaseHealth careEpidemiologyIntensive care medicineFamily medicineCancerEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

CONTEXT: Disease-specific registries that enroll a considerable number of patients play a major role in prostate cancer (PCa) research. OBJECTIVE: To evaluate available registries, describe their strengths and limitations, and discuss the potential future role of PCa registries in outcomes research. EVIDENCE ACQUISITION: We performed a literature review of the Medline, Embase, and Web of Science databases. The search strategy included the terms prostate cancer, outcomes, statistical approaches, population-based cohorts, registries of outcomes, and epidemiological studies, alone or in combination. We limited our search to studies published between January 2005 and January 2015. EVIDENCE SYNTHESIS: Several population-based and prospective disease-specific registries are currently available for prostate cancer. Studies performed using these data sources provide important information on incidence and mortality, disease characteristics at presentation, risk factors, trends in utilization of health care services, disparities in access to treatment, quality of care, long-term oncologic and health-related quality of life outcomes, and costs associated with management of the disease. Although data from these registries have some limitations, statistical methods are available that can address certain biases and increase the internal and external validity of such analyses. In the future, improvements in data quality, collection of tissue samples, and the availability of data feedback to health care providers will increase the relevance of studies built on population-based and disease-specific registries. CONCLUSIONS: The strengths and limitations of PCa registries should be carefully considered when planning studies using these databases. Although randomized controlled trials still provide the highest level of evidence, large registries play an important and growing role in advancing PCa research and care. PATIENT SUMMARY: Several population-based and prospective disease-specific registries for prostate cancer are currently available. Analyses of data from these registries yield information that is clinically relevant for the management of patients with prostate cancer.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.054
GPT teacher head0.359
Teacher spread0.305 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations69
Published2015
Admission routes1
Has abstractyes

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