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Record W4389486100 · doi:10.7759/cureus.50150

Prostate Cancer in the Caribbean

2023· review· en· W4389486100 on OpenAlexaff
Nuneaton S Ramesar, Amalia Hosein, Kristy Samaroo, Jameel Ali

Bibliographic record

VenueCureus · 2023
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineScopusIncidence (geometry)Caribbean regionProstate cancerPopulationCancerEpidemiologyHealth careMEDLINEEnvironmental healthFamily medicineLatin AmericansPathologyEconomic growthInternal medicine

Abstract

fetched live from OpenAlex

Prostate cancer (PC) is one of the principal causes of cancer death worldwide. The mortality rate for PC in the Caribbean is higher than in many developed countries, and there is a difference in the incidence among the various Caribbean nations. Besides surveillance and screening, these factors increase concerns about genetic and other risk factors causing PC incidence. PC research is limited in scope and regularity in the Caribbean, creating a literature gap. This literature review aims to examine the PC situation in the Caribbean to highlight where further studies are needed. This review includes all available studies on PC in the specified Caribbean population from 1958 to 2023 utilising the keywords "Prostate Cancer and Caribbean" on PubMed, Scopus, and ScienceDirect databases. The information is then structured by Caribbean countries and by seven themes. These themes are PC incidence and mortality, demographics, clinicopathology, genetics, non-genetic risks, diagnosis and treatment, and PC control. The findings demonstrated that countries with low resources are burdened by more severe illnesses with worse PC outcomes. Furthermore, territories with national cancer registries seemed to have enhanced methods for PC management. In conclusion, this review is significant because it provides initial support for researchers, administrators, and planners for PC healthcare. Additionally, it gives an opportunity for further epidemiological analyses that can supply more significant insights into the PC situation in the Caribbean. Further research should focus on prevention strategies and the standardisation of treatment procedures to enhance surveillance and improve patient outcomes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score0.580

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 integrity0.0000.000
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 head0.115
GPT teacher head0.420
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2023
Admission routes1
Has abstractyes

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