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Clinical impact of the Mexican healthcare system "Seguro Popular" on breast cancer survival.

2019· article· en· W2947059432 on OpenAlexaff
Luis Antonio Cancel, Carlos Eduardo Salazar-Mejía, Francisco Emilio Vera Badillo, Juan Francisco González-Guerrero, Jackeline Grace Lara-Campos, Lorena Itzel González-Palau, Blanca Otilia Wimer-Castillo, Óscar Vidal-Gutiérrez, José Luis Vela, Diego A Jaime-Villalon

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineBreast cancerHealth careCohortHealthcare systemClinical endpointRetrospective cohort studyFamily medicineSocial securityCancerInternal medicineClinical trialEconomic growth

Abstract

fetched live from OpenAlex

6569 Background: Breast cancer (BC) is one of the leading issues in public health in low and middle-income countries. In Mexico, access to healthcare is fragmented according to the patient´s employment and not by its needs; IMSS and ISSTE (Social Security) provide access to prepaid medicine to those under the formal sector of the economy, leaving up to 50 million Mexicans without access to a prepaid scheme. In 2003, the Seguro Popular (SP) was created in order to bring universal access to prepaid medicine in Mexico, and in 2007 expanded its coverage for BC. Methods: Retrospective and comparative study. The primary endpoint was to determine the impact on survival of SP on BC. Records were obtained from the electronic database of the Hospital Universitario “Dr. José Eleuterio González”. We included patients with invasive BC stage I-IV. Patients with any other kind of healthcare schemes other than SP, patients who underwent treatment outside our institution, and those with a follow up no greater than 3 months were excluded. 104 patients from the period prior the implementation of the SP (2000-2007) met the criteria for evaluation; thereafter we randomly selected a second cohort with the same size from the period after the implementation of the SP (2008-2013). Results: Median age at diagnosis was 48 and 51 years, respectively, for the periods before and after the implementation of SP. Distribution by clinical stage (Non-SP vs SP): CS I, 4.8 vs 10%, CS II, 31 vs 44%, CS III, 52 vs 38%, and CS IV, 10 vs 6.7%. Molecular subtypes distribution (Non-SP vs SP): Luminal, 61 vs 62%, HER2 Positive (IHC+++/FISH+) 17 vs 22%, TNBC, 21 vs 18%, unknown 6.7 vs 5.7%. Regarding survival, we observed a statistically significant difference on progression-free survival and overall survival favoring the SP cohort; PFS at 5 years, 54 vs 81% (p = < 0.0001) and OS at 5-year, 72 vs 86% (p = 0.01). Conclusions: We present evidence that the Mexican healthcare scheme SP, created to bring medical access to those patients without prepaid health protection, provides a significant clinical benefit on survival (PFS and OS) in women with breast 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 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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.202
GPT teacher head0.523
Teacher spread0.321 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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