MétaCan
Menu
Back to cohort
Record W2979129329 · doi:10.1093/annonc/mdz398

Efficacy of adoptive therapy with tumor-infiltrating lymphocytes and recombinant interleukin-2 in advanced cutaneous melanoma: a systematic review and meta-analysis

2019· review· en· W2979129329 on OpenAlexaff
U. Dafni, Olivier Michielin, Silvia Martin Lluesma, Zoi Tsourti, Varvara Polydoropoulou, Dimitris Karlis, Michal J. Besser, John B.A.G. Haanen, Pamela S. Ohashi, Udai S. Kammula, Angela Orcurto, Stefan Zimmermann, Lionel Trueb, Christopher A. Klebanoff, Michael T. Lotze, Lana E. Kandalaft, George Coukos

Bibliographic record

VenueAnnals of Oncology · 2019
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersCentre Hospitalier Universitaire VaudoisUniversité de LausanneNational Cancer InstituteLudwig Institute for Cancer Research
KeywordsMedicineMeta-analysisMelanomaInternal medicineOncologyConfidence intervalInterleukin 2ImmunotherapyClinical endpointAldesleukinSurgeryGastroenterologyClinical trialCancerCytokineCancer research

Abstract

fetched live from OpenAlex

Adoptive cell therapy (ACT) using autologous tumor-infiltrating lymphocytes (TIL) has been tested in advanced melanoma patients at various centers. We conducted a systematic review and meta-analysis to assess its efficacy on previously treated advanced metastatic cutaneous melanoma. The PubMed electronic database was searched from inception to 17 December 2018 to identify studies administering TIL-ACT and recombinant interleukin-2 (IL-2) following non-myeloablative chemotherapy in previously treated metastatic melanoma patients. Objective response rate (ORR) was the primary end point. Secondary end points were complete response rate (CRR), overall survival (OS), duration of response (DOR) and toxicity. Pooled estimates were derived from fixed or random effect models, depending on the amount of heterogeneity detected. Analysis was carried out separately for high dose (HD) and low dose (LD) IL-2. Sensitivity analyses were carried out. Among 1211 records screened, 13 studies (published 1988 - 2016) were eligible for meta-analysis. Among 410 heavily pretreated patients (some with brain metastasis), 332 received HD-IL-2 and 78 LD-IL-2. The pooled overall ORR estimate was 41% [95% confidence interval (CI) 35% to 48%], and the overall CRR was 12% (95% CI 7% to 16%). For the HD-IL-2 group, the ORR was 43% (95% CI 36% to 50%), while for the LD-IL-2 it was 35% (95% CI 25% to 45%). Corresponding pooled estimates for CRR were 14% (95% CI 7% to 20%) and 7% (95% CI 1% to 12%). The majority of HD-IL-2 complete responders (27/28) remained in remission during the extent of follow-up after CR (median 40 months). Sensitivity analyses yielded similar results. Higher number of infused cells was associated with a favorable response. The ORR for HD-IL-2 compared favorably with the nivolumab/ipilimumab combination following anti-PD-1 failure. TIL-ACT therapy, especially when combined with HD-IL-2, achieves durable clinical benefit and warrants further investigation. We discuss the current position of TIL-ACT in the therapy of advanced melanoma, particularly in the era of immune checkpoint blockade therapy, and review future opportunities for improvement of this approach.

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.024
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.199
GPT teacher head0.450
Teacher spread0.252 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations253
Published2019
Admission routes1
Has abstractno

Explore more

Same venueAnnals of OncologySame topicCAR-T cell therapy researchFrench-language works237,207