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Record W4311737282 · doi:10.1093/ofid/ofac492.108

1585. Efficacy and safety of long-acting subcutaneous lenacapavir in heavily treatment-experienced people with multi-drug resistant HIV: Week 52 results

2022· article· en· W4311737282 on OpenAlexaboutno aff
Onyema Ogbuagu, Sorana Segal‐Maurer, Winai Ratanasuwan, Benoît Trottier, Jason Brunetta, Takuma Shirasaka, Ellen Koenig, Hui Wang, Nicolas Margot, Hadas Dvory‐Sobol, Martin S. Rhee, Jared M. Baeten, Jean‐Michel Molina

Bibliographic record

VenueOpen Forum Infectious Diseases · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRegimenPlaceboViral loadInternal medicineRandomized controlled trialAdverse effectHuman immunodeficiency virus (HIV)GastroenterologyImmunology

Abstract

fetched live from OpenAlex

Abstract Background Lenacapavir (LEN), a potent first-in-class inhibitor of HIV-1 capsid function, is in development as a long-acting agent for treatment and prevention of HIV-1. Methods CAPELLA is an ongoing, phase 2/3 study in heavily treatment-experienced (HTE) people with HIV-1 (PWH) with multidrug-resistance. 36 participants were randomized (2:1) to add oral LEN or placebo to their failing regimen. At D15, those on oral LEN received subcutaneous (SC) LEN 927 mg (Q6M); those on placebo started the oral LEN lead-in, followed by SC Q6M. All randomized participants initiated an investigator-selected, optimized background regimen (OBR) at D15. An additional 36 participants started OBR concurrent with LEN (oral lead-in → SC) in a non-randomized cohort. We report the Week (W) 52 efficacy and safety results from both cohorts. Results Of 72 participants enrolled, 25% were female, 38% Black, median age 52 years, 64% had CD4 < 200 cells/µL, 46% had HIV-1 resistant to all 4 major classes (NRTI, NNRTI, PI, INSTI), and 53% had OBR with 1 or no fully active agents. At W52, 78% (56/72) achieved VL< 50 c/mL and 82% (59/72) achieved VL< 200 c/mL via FDA Snapshot algorithm. CD4 count increased by a median 84 cells/µL (Q1 to Q3: 21 to 153) and the proportion of participants with CD4 count ≥200 cells/ul increased from 36% at baseline to 68% at W52. Ten participants had emergent LEN resistance (8 previously reported); 4 of 10 subsequently suppressed. The median (range) duration of follow up on LEN was 71 (13–111) weeks. One participant discontinued due to injection site nodule (Grade 1). The most common injection site reaction (ISR) was swelling (28% [20/72] and 17% [12/70] after the 1st and 2nd SC doses, respectively). Most ISRs were mild or moderate. The most common AEs (excluding injection site reactions) were nausea and diarrhea (14% each). Conclusion In HTE PWH, subcutaneous LEN was well tolerated and in combination with OBR led to high and sustained rate of virologic suppression at W52. These results support the potential role for LEN for treatment of multi-drug resistant HIV-1 infection. Disclosures Sorana Segal-Maurer, MD, Gilead Sciences: Advisor/Consultant|Gilead Sciences: Grant/Research Support|Gilead Sciences: Honoraria|JANSSEN THERAPEUTICS: Honoraria|ViiV: Honoraria Benoit Trottier, MD, Gilead Sciences: Advisor/Consultant|Gilead Sciences: Honoraria|Merck: Advisor/Consultant|Merck: Honoraria|ViiV Healthcare: Advisor/Consultant|ViiV Healthcare: Honoraria Jason Brunetta, M.D., Gilead Canada: Advisor/Consultant|Gilead Canada: Honoraria|Gilead Canada: Conference Attendance Sponsorship|Viiv Canada: Advisor/Consultant Hui Wang, PhD, Gilead Sciences: Employment|Gilead Sciences: Stocks/Bonds Nicolas A. Margot, MA, Gilead Sciences: Employment|Gilead Sciences: Stocks/Bonds Hadas Dvory-Sobol, PhD, Gilead Sciences: Employment|Gilead Sciences: Stocks/Bonds Martin S Rhee, MD, Gilead Sciences: Stocks/Bonds Jared Baeten, MD, PhD, Gilead Sciences: Employee|Gilead Sciences: Stocks/Bonds Jean-Michel Molina, MD; PhD, GIlead: Board Member|GIlead: Grant/Research Support|Merck: Board Member|Merck: Expert Testimony|ViiV: Board Member.

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 score0.090
Threshold uncertainty score0.999

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 studies0.0010.000
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 head0.014
GPT teacher head0.272
Teacher spread0.259 · 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".

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Citations10
Published2022
Admission routes1
Has abstractyes

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