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Record W4389276416 · doi:10.18103/mra.v11i11.4752

Breast Cancer Screening in Latin America: The Challenge to Move from Opportunistic to Organized-Systematic Screening

2023· article· en· W4389276416 on OpenAlexaboutno aff
Klaus Püschel, Paz S, Marsha D. Fowler, Z Vescovic, Ignacia Fuentes, César Sánchez, Francisco Acevedo

Bibliographic record

VenueMedical Research Archives · 2023
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
FundersFondo de Financiamiento de Centros de Investigación en Áreas PrioritariasAgencia Nacional de Investigación y Desarrollo
KeywordsLatin AmericansMedicineBreast cancerDemographyCancerMortality rateBreast cancer screeningGeographyMammographyPolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

Background: Breast cancer is the leading cause of death from cancer among women in Latin America. Most Latin American countries started national mammogram screening programs a decade ago. The implementation level and effects of screening programs in Latin America have not been evaluated. Aim: To evaluate the association between screening programs implementation and breast cancer mortality in selected North American and European countries compared to a group of Latin American countries with national screening programs. Methods: The study applied an ecological design with secondary data from official national and international sources. Join point regression analysis was conducted to describe the trends in mortality rates in a group of five Latin American countries (Brazil, Chile, Colombia, Costa Rica and Mexico) with five Non-Latin American countries (Canada, Spain, Sweden, United Kingdom and the United States of America). The association between screening and mortality rates was explored using correlation and linear regression. National cancer plans were assessed to describe screening strategies among selected countries. Results: A significant reduction in standardized breast cancer mortality rates was observed in all Non-Latin American countries with an Average Annual Percent Change (AAPC) of -2.00 (p<.05, 95%CI [-3.33, -0.70]) for the period 2010-2020. In contrast, Latin American countries reported a significant increase in the AAPC of +1.38 (p<.05, 95%CI [0.86,1.76]) in breast cancer mortality rates for the period 2010-2020. For Latin American countries, with screening rates below 50%, there was no correlation between screening and mortality rates for the period 1985-2020 (r = -0.17, p = .78). For non-Latin American countries, with screening rates over 70%, the linear regression model explained significantly 55% of the variance in mortality rates (R2aj =.55, F (5,14) = 5.69, p = .005), with a negative and significant effect of mammogram screening on mortality rates (β = -0.14, p = .01). The National Plans analysis revealed an opportunistic screening model for Latin American countries and an organized-systematic model in Non-Latin American countries. Conclusion: There is an association between the level of implementation of screening programs and mortality rates from breast cancer. Latin American countries should transform their opportunistic strategy into an organized-systematic model.

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)0.053
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.058
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0050.004
Open science0.0030.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.227
GPT teacher head0.448
Teacher spread0.221 · 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 designObservational
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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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