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Record W7128473249 · doi:10.1177/108155890004800309

Time-Dependence of Survival Predictions Based on Markers of HIV Disease

2000· article· en· W7128473249 on OpenAlexaff
T. Perneger, Michał Abrahamowicz, Gillian Bartlett

Bibliographic record

VenueJournal of Investigative Medicine · 2000
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsCohortProportional hazards modelCohort studyStage (stratigraphy)Relative riskHuman immunodeficiency virus (HIV)Survival analysisProspective cohort study

Abstract

fetched live from OpenAlex

To determine whether the ability of baseline clinical stage, viremia, and CD4 cell counts to predict mortality in HIV-1-infected patients changes with duration of follow-up. Three hundred ninety-four patients were followed for an average of 29 months by the Swiss HIV Cohort Study, a practice-based registry of HIV-1-infected patients in Switzerland. Predictor variables were the baseline clinical stage, CD4 cell count, circulating HIV-1 RNA level, and the RNA/CD4 ratio; the outcome was death. The changes in relative risks of death over time were examined using survival models that extend the Cox model to allow for nonproportionality of hazards. During 949 person-years of follow-up, 169 patients died (mortality rate 17.8 per 100 person-years). Compared with clinical stage A, patients in stages B and C at baseline had much higher mortality rates in the subsequent year. The prognostic ability of stage C decayed over time (P=0.03). By contrast, the relative risks associated with a 2-fold difference in CD4 counts remained remarkably stable, at ~0.6 (P=0.81 for the time-dependence test). Relative hazards associated with a 10-fold difference in HIV RNA per milliliter and in HIV RNA per CD4 cell both tended to increase over time, but this trend failed to reach statistical significance (P=0.21 and P=0.08, respectively). Time-dependence patterns of prognostic ability varied widely among predictors, displaying gradual decay (clinical stage), stability (CD4 cells), and a trend to progressive increase (viremia). These results may affect clinical monitoring of HIV-infected patients and the interpretation of cohort studies of HIV-infected patients.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.025
GPT teacher head0.272
Teacher spread0.247 · 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 designBench or experimental
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

Citations0
Published2000
Admission routes1
Has abstractyes

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