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A phase II multicenter study of stereotactic radiotherapy (SRT) for oligoprogression in metastatic renal cell cancer (mRCC) patients receiving tyrosine kinase inhibitor (TKI) therapy.

2020· article· en· W3031007885 on OpenAlexafffund
Patrick Cheung, Samir Patel, Scott North, Arjun Sahgal, William Chu, Hany Soliman, Belal Ahmad, Eric Winquist, François Patenaude, Tamim Niazi, Daniel Yick Chin Heng, Arbind Dubey, Piotr Czaykowski, Rebecca Wong, Anand Swaminath, Scott C. Morgan, Justin White, Sareh Keshavarzi, Georg A. Bjarnason

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsSunnybrook HospitalOzmosis Research (Canada)McMaster UniversityJuravinski Cancer CentreBaker Hughes (Canada)Princess Margaret Cancer CentreUniversity of CalgaryMcGill University Health CentreMcGill UniversitySunnybrook Health Science CentreJewish General HospitalFoothills Medical CentreUniversity of AlbertaOttawa HospitalCancerCare ManitobaHealth Sciences CentreCancer Care Ontario
FundersPfizer Canada
KeywordsMedicineSunitinibPazopanibInternal medicineRenal cell carcinomaOncologyCancerCumulative incidenceSurgeryCohort

Abstract

fetched live from OpenAlex

5065 Background: SRT is increasingly considered to delay the need to change systemic therapy in metastatic cancer patients who develop oligoprogression. This prospective phase II study evaluated the use of SRT in the setting of mRCC patients who developed oligoprogression while on 1st or 2nd line TKI therapy. Methods: IMDC favourable or intermediate risk mRCC patients (pts) who had previous stability or response on ≥ 3 months of TKI therapy were eligible if they developed radiographic progression of ≤ 5 metastases. The oligoprogressive tumours were treated with SRT while other metastases which were stable or responding to TKI therapy were left alone. TKI therapy was temporarily stopped during SRT, and the same TKI drug then resumed. Endpoints included local control of the irradiated lesions, progression free survival (PFS), overall survival (OS), and cumulative incidence of changing systemic therapy after study entry. Results: 37 pts (median age 63, IMDC favourable 12, intermediate 25) with 57 oligoprogressive tumours were enrolled. 35 pts were on sunitinib and 2 on pazopanib. Median duration of TKI therapy prior to study entry was 18.6 months. 4 pts had IL-2 therapy prior to a 2nd line TKI. 21 pts had a solitary oligoprogressive tumour, while 17 pts had 2-3 oligoprogressive tumours treated with SRT. Median biological effective dose (BED10) was 72 Gy, corresponding to an SRT dose of 40 Gy in 5 fractions. Irradiated tumour sites were the following: 21 lung/pleural, 15 bone, 7 lymph node, 4 adrenal, 4 liver, 3 brain, 2 spleen, and 1 pancreas. At a median followup of 11.6 (1.8-53.5) months the median PFS from study entry was 9.6 months (95%CI 7.4-20.5) with the vast majority of progression occurring outside of the irradiated areas. The 2-year local control of the irradiated tumours was 96%. The 2-year OS from study entry was 77%. The cumulative incidence of changing systemic therapy was 47% at 1 year and 75% at 2 years, with a median time to a change in systemic therapy of 12.6 months. There were no grade 3-5 SRT related toxicities. Conclusions: To our knowledge, this is the first prospective evaluation of the use of SRT for oligoprogressive metastatic cancer. Local control of irradiated oligoprogressive mRCC tumours was high. After delivering SRT, mRCC patients did not need a change in their systemic therapy for a median of 1 year, effectively increasing the PFS of their TKI therapy. This novel approach should be studied in patients with oligoprogression on immunotherapy. Clinical trial information: NCT02019576 .

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)0.002
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.154
GPT teacher head0.472
Teacher spread0.318 · 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 designNon-randomized 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

Citations9
Published2020
Admission routes2
Has abstractyes

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