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Record W1872826128 · doi:10.1093/ofid/ofv071

Combination Therapy for Human Immunodeficiency Virus-Associated Cryptococcal Meningitis: Whom, When, and Where?

2015· article· en· W1872826128 on OpenAlexafffund
Mark J. Siedner, Jeffrey I. Campbell, Steve Kanters, John E. Bennett, Kristian Thorlund, Alexander C. Tsai, Edward J. Mills

Bibliographic record

VenueOpen Forum Infectious Diseases · 2015
Typearticle
Languageen
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsMcMaster UniversityUniversity of British ColumbiaUniversity of Ottawa
FundersFaculty of Health Sciences, University of OttawaMbarara University of Science and TechnologyNational Institutes of HealthMcMaster UniversityNational Institute of Mental HealthUniversity of OttawaMassachusetts General Hospital
KeywordsFlucytosineMedicineOdds ratioMeta-analysisConfidence intervalAmphotericin BRandomized controlled trialInternal medicineClinical endpointIntensive care medicineAntifungal

Abstract

fetched live from OpenAlex

To the editor—We appreciate the thoughtful comments raised by Wolbers and Day [1] in response to our article [2]. We agree with their primary point—that our meta-analysis summarized data across studies, and it is therefore best suited to evaluate study-level and not individual-level predictors of outcomes. We should have specified more clearly that our analysis is best suited for drawing inferences about relationships among patient populations, but not about individual patients. Indeed, this point is true for almost all meta-analysis, and it also applies to most individual randomized trials [3]. It is important to note that we did not intend to imply that combination amphotericin B and flucytosine conferred a benefit in patients with cryptococcal meningitis with altered mental status. Rather, in our meta-analysis, we were unable to identify a statistically significant treatment benefit across all published literature, for combination amphotericin B with flucytosine over amphotericin B alone. Although there was some implication of a benefit from adjunctive flucytosine in a subanalysis limited to studies that included patients with altered levels of consciousness, this estimate was not statistically significant (odds ratio = 0.56; 95% confidence interval [CI], .23–1.43) (Figure 1). As such, we hypothesized in the discussion that populations with altered consciousness might be more likely to benefit from adjunctive flucytosine therapy. If this hypothesis were correct, it would require patient-level data for confirmation. Forrest plot from network meta-analysis comparing odds of early (2-week) and late (10-week) mortality between combination amphotericin B and flucytosine with amphotericin B alone for human immunodeficiency virus-associated cryptococcal meningitis. Abbreviations: AmB, amphotericin B; 5FC, flucytosine; CI, confidence interval. In their recent large, randomized trial, Day et al [4] demonstrated superiority of combination amphotericin B and flucytosine over amphotericin B alone at 10 weeks. They now present a subanalysis with patient-level data that suggests that those with a normal Glasgow Coma Score (GCS) appeared to derive as much benefit (if not more) from the addition of flucytosine as those with a GCS < 15. Although their study was not powered to detect differences in these subgroups, their data do lend support to the use of flucytosine in individual patients with normal mental status within their study population. It should be noted that the overall mortality in their study was 36% at 10 weeks (and 30% among those who received amphotericin B and flucytosine combination therapy). In contrast, the only other large randomized trial to compare amphotericin B alone with amphotericin B and adjunctive flucytosine found no difference in mortality between groups at 10 weeks (6.7% versus 6.9%; relative risk = 0.97; 95% CI, .46–2.04) [5]. It is noteworthy that this other study was conducted in the United States, excluded comatose patients from enrollment, and had a lower prevalence of participants with altered mental status than the Day et al [4] study (11% vs 28%). We believe that the contrasting data from these 2 studies are in line with our overall conclusion: that current available evidence suggests that the adjunctive use of flucytosine might be beneficial in populations with advanced disease who are at high overall risk for mortality. As Wolbers and Day [4] point out, this does not necessarily mean that patients with normal mental status will not benefit from adjunctive flucytosine, only that populations with low overall risk of mortality are less likely to benefit. Unfortunately, for the time being, it appears that flucytosine is largely only available and in use in the areas of the world where the current data suggest it has the least benefit, whereas populations with the highest mortality often cannot access it [6, 7]. Indeed, the most important conclusion we draw from our study is that more data is required, across a range of patient populations and disease stages, to elucidate which drugs are needed for which patients, and to ensure that the optimal therapies are available to those who need them.

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)0.012
metaresearch head score (Gemma)0.077
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 score0.012
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.077
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0050.001
Research integrity0.0100.016
Insufficient payload (model declined to judge)0.0060.002

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 head0.036
GPT teacher head0.328
Teacher spread0.292 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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