MétaCan
Menu
Back to cohort
Record W4387774241 · doi:10.3390/curroncol30100665

Toxicities and Quality of Life during Cancer Treatment in Advanced Solid Tumors

2023· article· en· W4387774241 on OpenAlexvenueno aff
Eun Mi Lee, Paula Jiménez‐Fonseca, Rocío Galán-Moral, Sara Coca‐Membribes, Ana Fernández Montés, Elena Sorribes, Esmeralda García‐Torralba, Laura Puntí-Brun, Mireia Gil-Raga, Juana María Cano-Cano, Caterina Calderón

Bibliographic record

VenueCurrent Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsnot available
FundersSociedad Española de Oncología MédicaAstraZeneca
KeywordsMedicineCancerQuality of life (healthcare)Solid tumorCancer researchOncologyInternal medicineNursing

Abstract

fetched live from OpenAlex

The purpose of the study was to identify subgroups of advanced cancer patients who experienced grade 3-4 toxicities as reported by their oncologists as well as identify the demographic, clinical, and treatment symptom characteristics as well as QoL outcomes associated with distinct profiles of each patient. A prospective, multicenter, observational study was conducted with advanced cancer patients of 15 different hospitals across Spain. After three months of systemic cancer treatment, participants completed questionnaires that evaluated psychological distress (BSI-18), quality of life (EORTC QLQ-C30) and fatigue (FAS). The most common tumor sites for the 557 cancer patients with a mean age of 65 years were bronchopulmonary, digestive, and pancreas. Overall, 19% of patients experienced high-grade toxicities (grade 3-4) during treatment. Patients with recurrent advanced cancer, with non-adenocarcinoma cancer, undergoing chemotherapy, and a showing deteriorated baseline status (ECOG > 1) were more likely to experience higher toxicity. Patients who experienced grade 3-4 toxicities during cancer treatment had their treatment suspended in 59% of the cases. Additionally, 87% of the patients had a dose adjustment or a cycle delayed in their treatment due to a high risk of dying during treatment. Future research should focus on identifying interventions to reduce high-grade toxicities and improve quality of life in cancer 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.214
GPT teacher head0.518
Teacher spread0.305 · 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.

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

Citations37
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCurrent OncologySame topicCancer Treatment and PharmacologyFrench-language works237,207