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Record W2607356460 · doi:10.1186/s12885-017-3229-1

Overview of cancer incidence and mortality among people living with HIV/AIDS in British Columbia, Canada: Implications for HAART use and NADM development

2017· article· en· W2607356460 on OpenAlexaffabout
Connie G. Chiu, Danielle M. Smith, Kate Salters, Wendy Zhang, Steve Kanters, David J. Milan, Joan Montaner, Andy Coldman, Robert S. Hogg, Sam M. Wiseman

Bibliographic record

VenueBMC Cancer · 2017
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsSimon Fraser UniversityBC Cancer AgencyProvidence Health CareSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicinePopulationIncidence (geometry)CancerSurgical oncologyPsychological interventionInternal medicineImmunologyOncologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: The objective of this study is to evaluate the incidence of non-AIDS defining malignancies (NADMs) among people living with HIV/AIDS (PLWHA) in British Columbia, focusing on clinical correlates, highly active antiretroviral therapy (HAART) use, and survival, in order to elucidate mechanisms for NADM development. METHODS: A retrospective population based analysis was carried out for individuals with HIV/AIDS that began their treatment between 1996 and 2008. RESULTS: There were 145 (2.95%) NADMs and 123 (2.50%) AIDS defining malignancies (ADMs) identified in 4918 PLWHA in the study population. NADMs were represented by a range of cancer types including, most commonly, lung cancer, followed by anal, breast, head/neck, prostate, liver, rectal, and renal cancers. PLWHA had a SIR of 2.05 (CI:1.73, 2.41) for the development of NADMs compared to individuals without an HIV/AIDS diagnosis in the general population. Independent factors significantly associated with a NADM were: male gender, older age, lower CD4 cell counts, previous NADM, absence of HAART (non-HAART versus HAART) and treatment during the early-HAART era (before 2000 versus after 2000). CONCLUSIONS: NADMs represent an important source of morbidity for PLWHA. Use of HAART with its associated improvement in immune-restoration, and tailored targeted cancer screening interventions, may be beneficial and improve outcomes in this unique patient population.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.038
GPT teacher head0.308
Teacher spread0.270 · 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 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

Citations45
Published2017
Admission routes2
Has abstractyes

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