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[<sup>177</sup>Lu]Lu-DOTA-TATE in newly diagnosed patients with advanced grade 2 and grade 3, well-differentiated gastroenteropancreatic neuroendocrine tumors: Primary analysis of the phase 3 randomized NETTER-2 study.

2024· article· en· W4391096671 on OpenAlexaff
Simron Singh, Daniel M. Halperin, Sten Myrehaug, Ken Herrmann, Marianne Pavel, Pamela L. Kunz, Beth Chasen, Jaume Capdevila, Salvatore Tafuto, Do‐Youn Oh, Changhoon Yoo, Stephen Falk, Þorvarður R. Hálfdánarson, Ilya Folitar, Yufen Zhang, Paola Santoro, Paola Aimone, Wouter W. de Herder, Diego Ferone

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineClinical endpointNeuroendocrine tumorsRadionuclide therapyNuclear medicineProgression-free survivalInternal medicineOctreotideRandomized controlled trialResponse Evaluation Criteria in Solid TumorsPhases of clinical researchGastroenterologyUrologySomatostatinClinical trialOverall survival

Abstract

fetched live from OpenAlex

LBA588 Background: Currently, there is no universally accepted first line (1L) therapy for higher grade, well-differentiated gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and an unmet medical need remains in these patients (pts). Radioligand therapy (RLT) is an innovative cancer treatment that crosses the traditional domains of systemic, radiation or surgical therapies. The Phase 3 NETTER-2 study (NCT03972488) evaluated [ 177 Lu]Lu-DOTA-TATE (hereafter 177 Lu-DOTATATE) as 1L treatment in pts with Grade (G) 2 and G3 advanced GEP-NETs. This is the first trial to assess 1L RLT in any solid tumor. Methods: Eligible pts were newly diagnosed with somatostatin receptor-positive high G2 or G3 (Ki-67 ≥10% and ≤55%) advanced GEP-NETs within the last 6 months prior to enrollment. Pts were randomized (2:1) to receive 4 cycles of 177 Lu-DOTATATE (4 × 7.4 GBq) plus 30 mg octreotide long-acting release (LAR) at 8-weekly intervals during 177 Lu-DOTATATE treatment then every 4 weeks ( 177 Lu-DOTATATE arm), or 60 mg octreotide LAR every 4 weeks (control arm), stratified by grade (G2 vs G3) and tumor origin (pancreas vs other). The primary endpoint was progression-free survival (PFS), centrally assessed using RECIST 1.1. Objective response rate (ORR), a key secondary endpoint, was tested hierarchically after PFS. Results: Overall, 226 pts were randomized to the 177 Lu-DOTATATE (n = 151) or control (n = 75) arms. Most tumors originated in the pancreas (54.4%) or small intestine (29.2%); G3 tumors were reported in 35.0% of pts. Median cumulative dose of 177 Lu-DOTATATE was 29.2 GBq, with 87.8% of pts receiving all 4 doses. Median PFS (95% confidence interval [CI]) was significantly prolonged by ~14.3 months from 8.5 months (7.7, 13.8) in the control arm to 22.8 months (19.4, not estimable) in the 177 Lu-DOTATATE arm; stratified hazard ratio 0.276 (95% CI: 0.182, 0.418; p &lt; 0.0001). The ORR was significantly higher in the 177 Lu-DOTATATE arm (43.0%) vs the control arm (9.3%); stratified odds ratio 7.81 (95% CI: 3.32, 18.4; p &lt; 0.0001). PFS and ORR results were consistent across all pre-specified demographic and prognostic subgroups. Among adverse events of special interest to RLT, G3/4 leukopenia, anemia and thrombocytopenia occurred in ≤3 pts each in the 177 Lu-DOTATATE arm. One case of myelodysplastic syndrome was reported ( 177 Lu-DOTATATE arm). Conclusion: 177 Lu-DOTATATE significantly prolonged PFS and demonstrated a clinically meaningful ORR, compared with high-dose octreotide LAR, in pts with newly diagnosed advanced G2 and G3 GEP-NETs. Safety was in line with the established profile of 177 Lu-DOTATATE. This is the first randomized study to demonstrate efficacy of RLT as 1L treatment in any malignancy and will change clinical practice. Further investigations of RLT as a therapeutic option in other settings is warranted. Clinical trial information: NCT03972488 .

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)0.004
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 score0.184
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.033
GPT teacher head0.403
Teacher spread0.370 · 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
Published2024
Admission routes1
Has abstractyes

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