MétaCan
Menu
Back to cohort

Assessment of chemotherapy-induced cognitive impairment: A prospective study of the biochemical and metabolic effects of platinum/taxane-based chemotherapy in gynecologic cancer patients.

2021· article· en· W3169843089 on OpenAlexaboutno aff
Megan Leigh Gleason Hutchcraft, Amelia J. Anderson‐Mooney, Emily V. Dressler, D. Allan Butterfield, Daret St. Clair, David K. Powell, Lisa Koehl, Frederick A. Schmitt, Brent J. Shelton, J Górski, Lauren Baldwin, Christopher P. DeSimone, Holly H. Gallion, Fredrick R. Ueland, Rachel W. Miller

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer-related cognitive impairment studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTaxaneChemotherapyInternal medicineOxidative stressOncologyMontreal Cognitive AssessmentCancerDocetaxelProspective cohort studyBreast cancerCognitive impairmentDisease

Abstract

fetched live from OpenAlex

e24051 Background: Chemotherapy-induced cognitive impairment (CICI) is a common side effect of cancer therapy, affecting up to 75% of cancer patients. Oxidative stress is thought to play a key role in CICI and patients who have been treated with chemotherapy have demonstrated biochemical brain changes on magnetic resonance spectroscopy (MRS). Methods: Following institutional review board approval, chemotherapy-naïve gynecologic cancer patients scheduled to receive intravenous platinum/taxane-based chemotherapy were identified. The primary objective of this study was identification of chemotherapy-induced cognitive function changes using the Montreal Cognitive Assessment (MoCA) tool. This exploratory analysis evaluates correlations between changes in MoCA scores, oxidative analytes TNF-a, protein carbonyls (PC), and 4-hydroxynonenal (HNE) protein adducts, and MRS metabolic signals. Testing was performed at baseline and three weeks post-treatment. Simple linear regression was performed to evaluate the correlation between changes in MoCA scores and oxidative metabolites. Results: Fourteen patients were enrolled. Six patients had complete pre/post oxidative stress data, and four patients had complete pre/post MRS data. Five of six had decreased PC values (mean net change -15.17%, SD 0.15), half had increased HNE levels (mean net change +16.38%, SD 0.38), and four of six had decreased TNF-a values (mean net change -15.10%, SD 0.27) (Table). MoCA scores were positively correlated with serum PC levels ( r = 0.86, p = 0.03) and not significantly correlated with TNF-a or HNE levels. Of those with complete pre/post MRS data, all patients had a decrease in glycerophosphocholine + phosphocholine/creatinine ratio signals. MoCA raw score prior to and after completion of chemotherapy. A higher score indicates improved test performance. Positive percentage of oxidative stress markers (PC, HNE, TNF-a) indicates increased post-therapy levels compared to pre-therapy. Conclusions: In this study, we evaluated candidate oxidative stress serum markers and changes in MRS metabolite signals for CICI. Serum PC levels correlate with cognitive screening scores. For patients undergoing brain imaging, MRS evaluation for individual choline components, glycerophosphocholine and phosphocholine, may serve as an additional marker of oxidative damage. This pilot study highlights the potential value of serum PC levels and dedicated brain imaging for signs of oxidative stress, including MRS, to guide future CICI identification studies. Clinical trial information: NCT03324945. [Table: see text]

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)0.002
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.036
GPT teacher head0.427
Teacher spread0.391 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicCancer-related cognitive impairment studiesFrench-language works237,207