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Record W4223938136 · doi:10.1002/cncr.34195

Real‐world analysis of main clinical outcomes in patients with polycythemia vera treated with ruxolitinib or best available therapy after developing resistance/intolerance to hydroxyurea

2022· article· en· W4223938136 on OpenAlexfundno aff
Alberto Álvarez‐Larrán, Marta Garrote, Francisca Ferrer‐Marín, Manuel Pérez‐Encinas, María‐Isabel Mata‐Vázquez, Beatríz Bellosillo, Eduardo Arellano‐Rodrigo, Montse Gómez, Regina García, Valentín García‐Gutiérrez, Mercedes Gasior Kabat, Beatriz Cuevas, Anna Angona, María Teresa Gómez‐Casares, Clara Martínez, Elena Magro, Rosa Ayala, Rafael Del Orbe, Raúl Pérez‐López, María Laura Fox, José‐María Raya, Lucía Guerrero, Carmen García‐Hernández, Gonzalo Caballero, Ilda Murillo, Blanca Xicoy, M.J. Ramírez, Gonzalo Carreño‐Tarragona, Juan Carlos Hernández‐Boluda, Arturo Pereira

Bibliographic record

VenueCancer · 2022
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsnot available
FundersInstituto de Salud Carlos IIISierra OncologySociedad Española de Hematología y HemoterapiaAstellas PharmaIncyteAstraZenecaCelgeneSanofi
KeywordsMedicineRuxolitinibPolycythemia veraInternal medicineMyelofibrosisIntensive care medicineBone marrow

Abstract

fetched live from OpenAlex

BACKGROUND: Ruxolitinib is approved for patients with polycythemia vera (PV) who are resistant/intolerant to hydroxyurea, but its impact on preventing thrombosis or disease-progression is unknown. METHODS: A retrospective, real-world analysis was performed on the outcomes of 377 patients with resistance/intolerance to hydroxyurea from the Spanish Registry of Polycythemia Vera according to subsequent treatment with ruxolitinib (n = 105) or the best available therapy (BAT; n = 272). Survival probabilities and rates of thrombosis, hemorrhage, acute myeloid leukemia, myelofibrosis, and second primary cancers were calculated according to treatment. To minimize biases in treatment allocation, all results were adjusted by a propensity score for receiving ruxolitinib or BAT. RESULTS: Patients receiving ruxolitinib had a significantly lower rate of arterial thrombosis than those on BAT (0.4% vs 2.3% per year; P = .03), and this persisted as a trend after adjustment for the propensity to have received the drug (incidence rate ratio, 0.18; 95% confidence interval, 0.02-1.3; P = .09). There were no significant differences in the rates of venous thrombosis (0.8% and 1.1% for ruxolitinib and BAT, respectively; P = .7) and major bleeding (0.8% and 0.9%, respectively; P = .9). Ruxolitinib exposure was not associated with a higher rate of second primary cancers, including all types of neoplasia, noncutaneous cancers, and nonmelanoma skin cancers. After a median follow-up of 3.5 years, there were no differences in survival or progression to acute leukemia or myelofibrosis between the 2 groups. CONCLUSIONS: The results suggest that ruxolitinib treatment for PV patients with resistance/intolerance to hydroxyurea may reduce the incidence of arterial thrombosis. LAY SUMMARY: Ruxolitinib is better than other available therapies in achieving hematocrit control and symptom relief in patients with polycythemia vera who are resistant/intolerant to hydroxyurea, but we still do not know whether ruxolitinib provides an additional benefit in preventing thrombosis or disease progression. We retrospectively studied the outcomes of 377 patients with resistance/intolerance to hydroxyurea from the Spanish Registry of Polycythemia Vera according to whether they subsequently received ruxolitinib (n = 105) or the best available therapy (n = 272). Our findings suggest that ruxolitinib could reduce the incidence of arterial thrombosis, but a disease-modifying effect could not be demonstrated for ruxolitinib in this patient population.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.334
Teacher spread0.299 · 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 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

Citations32
Published2022
Admission routes1
Has abstractyes

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