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Record W4408593829 · doi:10.1016/j.radonc.2025.110851

The prognostic and predictive value of pre-treatment hematologic markers for oropharyngeal carcinoma stratified by HPV status and treated with definitive (chemo) radiation

2025· article· en· W4408593829 on OpenAlexaff
A. Hughes, Chukwuwike Johnny, Shao Hui Huang, Jie Su, Scott V. Bratman, John Cho, Ezra Hahn, Ali Hosni, Andrew Hope, John Kim, Jason Sheng Horng Tsai, Brian O’Sullivan, J.G. Ringash, John Waldron, Anna Spreafico, Lawson Eng, E. Sanz García, John DeAlmeida, Tong Li, Wei Xu, Andrew McPartlin

Bibliographic record

VenueRadiotherapy and Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicinePredictive valueInternal medicineOncology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The literature of hematological biomarker performance in oropharynx cancer is conflicted, likely due to heterogeneity of the cohorts studied, limiting clinical application. To resolve this, we analyze the predictive and prognostic power of the pre-treatment hematologic markers total lymphocyte count (TLC), total neutrophil count (TNC), total monocyte count (TMC), and neutrophil-lymphocyte ratio (NLR), for a large oropharynx cohort receiving definitive (chemo)radiotherapy ((C)RT). MATERIALS AND METHODS: All OPC patients treated at a single academic center with definitive (C)RT between 2005-2018 were included. The actuarial rates of locoregional control (LRC) and distant control (DC) were calculated using competing risks methods, while overall survival (OS) was estimated using the Kaplan-Meier method. Multivariable analysis (MVA) was applied to assess the prognostic and predictive value of the TLC, TMC, TNC, and NLR, adjusted for known prognostic factors. A Bonferroni correction was applied with a significance threshold of p < 0.01, due to consideration of multiple markers. RESULTS: A total of 1,515 OPC patients were included (HPV-positive 1,151; HPV-negative 364). The median follow-up was 5.5 years, and 469 deaths were recorded. A significant interaction between the association of TLC and overall survival (OS) and the use of chemotherapy was identified for HPV-positive disease (p < 0.001). Hence, analysis was performed separately to determine the association of TLC with the outcome for the CRT and RT alone cohorts for HPV-positive OPC. On MVA, TLC was only prognostic for HPV-positive OPC when receiving CRT (OS adjusted HR (aHR) 0.51 (0.35-0.74), p < 0.001), with improved outcomes seen with higher TLC. TLC was also predictive for HPV-positive OPC, with a larger benefit to OS from the addition of concurrent cisplatin seen as TLC increased. On MVA, NLR, TNC, and TMC did not show a significant prognostic value in HPV-positive or HPV-negative OPC (p > 0.01 for all markers). CONCLUSION: In this large and homogenous cohort of OPC patients receiving definitive (C)RT, TLC was found to be a prognostic and predictive biomarker for patients with HPV-positive OPC receiving CRT, but not RT alone nor in HPV-negative disease. No other assessed marker was prognostic. TLC may inform the stratification of patients for investigation of novel treatment strategies in HPV-positive OPC. Prospective validation of this finding is required.

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)0.003
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.277
Teacher spread0.269 · 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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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