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Record W2327835887 · doi:10.1158/1538-7445.am2013-2376

Abstract 2376: Improved progression-free survival (PFS) in patients with short tumor telomere length: Subgroup analysis from a randomized phase II study of the telomerase inhibitor imetelstat as maintenance therapy for advanced NSCLC .

2013· article· en· W2327835887 on OpenAlexaff
Alberto Chiappori, Ekaterina Bassett, Bart Burington, Tatjana Kolevska, David R. Spigel, Steven Hager, Mark U. Rarick, Shirish M. Gadgeel, Normand Blais, Joachim von Pawel, Lowell L. Hart, Hui Wang, Kevin H. Eng, Martin Reck, Joan H. Schiller

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsHôpital Notre-Dame
Fundersnot available
KeywordsTelomeraseTelomereMedicineInternal medicineOncologyBiologyCancer researchGenetics

Abstract

fetched live from OpenAlex

Abstract Tumor regrowth after chemotherapy may be driven by growth of tumor ‘stem cells’. Telomerase, required for indefinite replication, is upregulated both in putative ‘stem cells’ and bulk tumor cells. Imetelstat, a lipidated 13-mer oligonucleotide, is a potent and specific inhibitor of telomerase. A randomized phase II study was conducted to assess whether imetelstat, given as maintenance therapy, prolongs PFS in advanced NSCLC: results for the primary and secondary endpoints are reported separately. NSCLC cell lines and other tumor cells with short telomeres appear to be more sensitive to imetelstat in vitro than those with long telomeres. A planned exploratory analysis to determine PFS as a function of tumor telomere length (TL) was performed. Tumor TL was assessed in archival tumor specimens from pts by quantitative PCR (qPCR). TL data were available for 57 of the 116 pts accrued in the clinical trial. PFS was evaluated in patients grouped into the shortest 1/2, shortest 1/3 and shortest 1/4 of TL. In 19 pts with the shortest 1/3 TL measured by qPCR, imetelstat maintenance increased PFS with a HR in favor of the imetelstat arm of 0.32 (95% CI 0.1 to 1.0), p=0.042 (un-stratified log rank). Median PFS was 4.0 months for the imetelstat-treated short TL sub-group and 1.5 months for the control short TL sub-group. In the 38 pts with the longest 2/3 TL HR was 0.83 (95% CI 0.36 to 1.9). Results in the group with the shortest 1/4 of TL were similar to the shortest 1/3 TL group, and in the shortest 1/2 group, results were consistent but attenuated, indicating that a smaller subset may contain patients with the most potential to benefit. In the control arm, short TL was associated with shorter median PFS (1.48 months) compared to patients with long TL (2.7 months), suggesting that short TL has a negative prognostic value. These findings suggest that imetelstat given as maintenance therapy prolongs PFS in pts with advanced NSCLC whose tumors have short telomeres as measured by qPCR. The data are consistent with the hypothesis that clinical benefit from telomerase inhibition is greater in patients with tumors possessing short telomeres. Prospective confirmation of these results in solid tumors and hematologic neoplasms is planned. Citation Format: Alberto Chiappori, Ekaterina Bassett, Bart Burington, Tatjana Kolevska, David R. Spigel, Steven Hager, Mark Rarick, Shirish Gadgeel, Normand Blais, Joachim Von Pawel, Lowell Hart, Hui Wang, Kevin Eng, Martin Reck, Joan Schiller. Improved progression-free survival (PFS) in patients with short tumor telomere length: Subgroup analysis from a randomized phase II study of the telomerase inhibitor imetelstat as maintenance therapy for advanced NSCLC . [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2376. doi:10.1158/1538-7445.AM2013-2376

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)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.029
GPT teacher head0.368
Teacher spread0.339 · 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 designRandomized trial
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

Citations1
Published2013
Admission routes1
Has abstractyes

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