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Patterns of response to anti-PD1 treatment: Comparison of three radiological response criteria and effect on overall survival (OS) in metastatic melanoma patients (MM).

2015· article· en· W2565812816 on OpenAlexaff
Minnie Kibiro, Leila Khoja, David Hogg, Marcus O. Butler, Ur Metser, Eshetu G. Atenafu, Anthony M. Joshua

Bibliographic record

VenueJournal of Clinical Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineInternal medicineRadiological weaponHazard ratioNuclear medicineResponse Evaluation Criteria in Solid TumorsPembrolizumabOncologyRadiologyProgressive diseaseCancerChemotherapyConfidence intervalImmunotherapy

Abstract

fetched live from OpenAlex

9073 Background: Radiological assessment of patterns of response (R) to checkpoint inhibitors remain imperfect. irRC accounts for pseudoprogression but does not evaluate change in density. We aimed to evaluate individual lesion and inter patient R by RECIST 1.1, irRC, CHOI and modified CHOI (mCHOI) and correlate R with OS. Methods: 37 patients (pts) with 567 measurable lesions treated with pembrolizumab in a phase 1 trial were studied. Bidimensional tumor diameter and density measurements were obtained at baseline and serial assessment CT scans. Overall R was assigned as per final CT scan assessment. Association of each criterion with OS was determined. Results: R varied according to site of metastases; lung lesions had the highest rate of complete response (CR) compared to other sites (69/163 (42%) lesions vs 71/404 (18%) p < .0001) and R varied at first assessment by RECIST compared to irRC (table). Delayed R post first scan were seen in 2/37 (5%) deemed PD by RECIST and 2/14 (14%) pts deemed PD by irRC at 1st assessment. 1/6 pts deemed to have PD by irRC at second assessment also had delayed R. 24 (65%) pts met CHOI density and size criteria for R at first follow-up. mCHOI criteria (> 15% density decrease and decrease in tumor size > 10%) showed R of 38% (14/37). Change in tumor size and density on 1st follow-up assessment was associated with OS with each 1000 mm2 increase in tumor size from baseline increasing the hazard of dying by 25.9% (HR = 1.259, [95% CI = 1.116-1.420], p = 0.0002). Similarly each 100HU increase in density increased the HR by 99% (HR = 1.99, [95% CI 1.246-3.176], p = 0.0039). R defined by any criteria had superior OS (CHOI, p = 0.0084; mCHOI, p = 0.0183; irRC, p < 0.0001 and RECIST, p = 0.0003). Conclusions: R by any criteria was prognostic and pseudoprogression was seen. The novel patterns of R and changes on treatment in tumor density suggest complex anti-tumor R of immunotherapy and require further validation. CR (%) PR/SD/PD (%) Site of Metastases Lung 42 58 Liver 24 76 Other solid organ 22 78 Peritoneal 37 63 Node 7 93 Subcutaneous 21 79 Other 11 89 R at first assessment scan RECIST 1.1 9/12/16 (24/32/44) irRC 10/13/14 (27/35/38)

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)0.001
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.145
GPT teacher head0.498
Teacher spread0.354 · 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".

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Citations1
Published2015
Admission routes1
Has abstractyes

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