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Management of pyrexia in metastatic melanoma patients: A real-world clinical experience survey study.

2020· article· en· W3029372856 on OpenAlexaff
Ambika Satija, A. Simon Pickard, Raluca Ionescu‐Ittu, François Laliberté, You‐Li Ling, Antônio Nakasato, Barinder Kang, Mei Sheng Duh, Jeetvan Patel

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsGroup for Research in Decision Analysis
FundersNovartis
KeywordsMedicineDabrafenibTrametinibAdverse effectInternal medicineMelanomaMetastatic melanomaVemurafenibOncologyCancer

Abstract

fetched live from OpenAlex

e22102 Background: Patients with BRAF+ metastatic melanoma (MM) have more options for treatment, including targeted therapy and immunotherapy. However, the risk of toxicities may contribute to lower treatment rates and duration. Pyrexia is a reversible adverse event commonly associated with BRAF/MEK inhibitors. However, little is known about the features, management strategies, as well as variations in pyrexia management in clinical practice. Methods: The study was conducted over two phases. Phase 1 was a qualitative study conducted with expert nurses to develop a pyrexia management questionnaire. The questionnaire was further enhanced through a pre-test with nurses to improve reliability and internal validity of the responses captured for this study. During Phase 2, a cross-sectional web-based questionnaire was administered to oncology registered nurses, nurse practitioners and physician assistants. All respondents were required to have managed pyrexia in patients with MM receiving dabrafenib+trametinib (D+T). Results: Respondents (N = 201, 57.2% academic center and 42.8% community based), on average, had 12.5 years of experience and >50% had managed more than 10 patients with BRAF-MEK inhibitor in the past 12 months. Almost all respondents (97.5%) discussed pyrexia with patients at D+T initiation. At the onset of the first episode of pyrexia in a patient, most respondents either try to keep patients on the starting dose (34.9% for D, 42.8% for T) or withhold the medication only temporarily (52.4% for D and 47.8% for T), even with a fever of 104°F. Mean time to treatment reinitiation was 1.5 days and, in more than half of the instances (52.3% for D and 51.4% for T), respondents would ask the patients to reinitiate at the starting dose. Respondents also asked patients to initiate antipyretics (87.5%) or corticosteroids (34.5%) to manage pyrexia symptoms. Even at pyrexia recurrence, respondents generally preferred keeping patients on treatment, with only 4.2% recommending permanent discontinuation. In general, respondents were very comfortable in managing pyrexia-related symptoms in their patients (mean score 7.8, 1 = very uncomfortable, 10 = very comfortable). Conclusions: In clinical practice, respondents were very comfortable in managing pyrexia. They tried to keep patients on D+T as long as possible. Experienced oncology nurses, nurse practitioners and physician assistants are able to manage pyrexia symptoms and keep patients on treatment for a longer duration to help obtain maximum clinical benefit.

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)0.004
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.202
GPT teacher head0.476
Teacher spread0.274 · 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".

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Citations2
Published2020
Admission routes1
Has abstractyes

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