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Record W2559773245 · doi:10.18553/jmcp.2016.16233

Duration of Treatment in Prostate Cancer Patients Treated with Abiraterone Acetate or Enzalutamide

2016· article· en· W2559773245 on OpenAlexaff
Dominic Pilon, Ajay S. Behl, Lorie Ellis, Bruno Émond, Patrick Lefèbvre, Nancy A. Dawson

Bibliographic record

VenueJournal of Managed Care & Specialty Pharmacy · 2016
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsGroup for Research in Decision Analysis
FundersGenentechAstellas PharmaJanssen Scientific AffairsRegeneron PharmaceuticalsNovo NordiskSanofiGlaxoSmithKlinePfizerAllerganBristol-Myers Squibb
KeywordsAbiraterone acetateEnzalutamideMedicineProstate cancerHazard ratioInternal medicineProportional hazards modelOncologyDocetaxelCancerUrologyGynecologyAndrogen deprivation therapyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Abiraterone acetate (AA) and enzalutamide (ENZ) are oral therapies offering survival benefit to metastatic castration-resistant prostate cancer (mCRPC) patients. Despite the availability of multiple treatment options for mCRPC, there is a lack of information on the effect that being initiated on AA or ENZ has on the combined prostate cancer treatment duration. OBJECTIVE: To compare the combined duration of prostate cancer treatments of patients initiated on AA with that of patients initiated on ENZ. METHODS: Truven Health MarketScan Research Databases from March 2012 to December 2014 were used to identify males with prostate cancer initiated on AA or ENZ (index therapy). Baseline characteristics were assessed during the 6 months pre-index. Inverse probability of treatment weights (IPTWs) were used to reduce baseline confounding. Treatment duration spanned from the index date to the earliest of treatment discontinuation (defined as a > 60-day gap in treatment), 24 months post-index, health plan disenrollment, or end of data. Weighted Kaplan-Meier and Cox proportional hazard models were used to compare the combined duration of mCRPC treatments (AA, ENZ, chemotherapy, sipuleucel-T, and radium 223) and any prostate cancer treatments (mCRPC, hormonal, and corticosteroid treatments) between patients initiated on either AA or ENZ. RESULTS: A total of 2,591 patients initiated on AA and 807 patients initiated on ENZ were selected for the study. Patients' characteristics were generally well balanced after IPTW. At 3 months, patients initiated on AA were associated with fewer discontinuations of mCRPC treatments (hazard ratio [HR] = 0.73, P = 0.004) or of any prostate cancer treatments (HR = 0.61, P = 0.002), compared with patients initiated on ENZ. This result was maintained at 6, 9, 12, 18, and 24 months for mCRPC treatments (HR = 0.75, P < 0.001) and for any prostate cancer treatments (HR = 0.69, P < 0.001). Median duration of mCRPC treatments was 4.1 months longer for patients initiated on AA compared with those initiated on ENZ (18.3 vs. 14.2 months, P < 0.001) and similarly, the median duration of any prostate cancer treatment was longer for patients initiated on AA compared with those initiated on ENZ (not reached vs. 22.2 months, P < 0.001). CONCLUSIONS: In this study, patients initiated on AA, compared with those initiated on ENZ, had a longer combined duration of mCRPC or prostate cancer treatments. DISCLOSURES: This research was funded by Janssen Scientific Affairs. Pilon, Emond, and Lefebvre are employees of Analysis Group, a consulting company that has received research grants from Janssen Scientific Affairs. Behl and Ellis are employees of Janssen Scientific Affairs and stockholders in Johnson & Johnson. Dawson is on the speakers bureau for Janssen, Astellas, and Sanofi Aventis. Emond reports grants from Regeneron, Bristol-Myers Squibb, GlaxoSmithKline, Aegerion, Bayer, Novartis, Allergan, Millenium, and Genentech. Pilon reports grants from Novartis, GlaxoSmithKline, Pfizer, and Bayer. Lefebvre reports grants from GlaxoSmithKline, Novartis, Bayer, Medtronic, Noven, and Novo Nordisk. Study concept and design were contributed primarily by Pilon and Lefebvre, along with the other authors. Pilon, Emond, and Lefebre collected the data, and data interpretation was performed by Behl, Lefebvre, and Dawson, along with Pilon, Ellis, and Emond, The manuscript was written by Pilon, Emond, and Lefebvre and revised by Behl, Ellis, and Dawson.

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 score0.297
Threshold uncertainty score0.443

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 head0.030
GPT teacher head0.343
Teacher spread0.313 · 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".

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Citations17
Published2016
Admission routes1
Has abstractyes

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