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Record W4406213122 · doi:10.1097/moh.0000000000000859

Red blood cell changes due to cancer and cancer treatments: a narrative review

2025· review· en· W4406213122 on OpenAlexaff
Deirdre Finnigan, Omar Hajjaj, Maha Othman

Bibliographic record

VenueCurrent Opinion in Hematology · 2025
Typereview
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsSt. Lawrence CollegeQueen's University
Fundersnot available
KeywordsMean corpuscular volumeCancerHematocritPolyunsaturated fatty acidMedicineAnemiaInternal medicineHemoglobinMean corpuscular hemoglobinRed blood cellPhysiologyOncologyGastroenterologyFatty acidBiologyBiochemistry

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To date, there is relatively limited research investigating changes in red blood cells (RBCs), particularly qualitative changes, in cancer patients and cancer patients receiving treatment. These changes may be important in better understanding cancer-associated anemia, which is the most prevalent hematological disorder in cancer patients with wide-ranging implications on patient care and quality of life. This review aims to summarize available evidence regarding qualitative and quantitative changes in RBCs in individuals with cancer prior to treatment and in patients undergoing treatment. RECENT FINDINGS: The most commonly reported changes in RBCs in cancer patients were increased mean corpuscular volume (MCV) and decreased hemoglobin, RBC count, and hematocrit. There were increased lipid peroxidation products and decreased antioxidants. There were increased polyunsaturated fatty acids (PUFAs) and decreased monounsaturated fatty acids (MUFAs) and saturated fatty acids (FAs). Additionally, RBC shape alterations with various atypical morphologies, membrane structure abnormalities, and impaired fluidity were also reported. These and various other reported findings are discussed in depth. SUMMARY: There are several reported quantitative and qualitative RBC changes in individuals with cancer, with some studies exhibiting conflicting results. Further research is needed to solidify the data and to better understand hematological-associated comorbidities in those patients.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.588
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
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 head0.081
GPT teacher head0.441
Teacher spread0.360 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2025
Admission routes1
Has abstractyes

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