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Record W2885976838 · doi:10.18553/jmcp.2018.24.8.759

Projecting the Potential Effect of Using Paliperidone Palmitate Once-Monthly and Once-Every-3-Months Long-Acting Injections Among Medicaid Beneficiaries with Schizophrenia

2018· article· en· W2885976838 on OpenAlexaff
Anirban Basu, Carmela Benson, Larry Alphs

Bibliographic record

VenueJournal of Managed Care & Specialty Pharmacy · 2018
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsInstitute of Health Economics
FundersJanssen Scientific Affairs
KeywordsPaliperidone PalmitateMedicineMedicaidSchizophrenia (object-oriented programming)AntipsychoticDiscontinuationPaliperidonePopulationRandomized controlled trialInclusion and exclusion criteriaInternal medicinePsychiatryEnvironmental healthAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Once-monthly and once-every-3-months long-acting injectable (LAI) formulations of paliperidone palmitate (PP1M and PP3M, respectively) are available for the treatment of patients with schizophrenia. However, information on the comparative effectiveness and costs of using these LAIs versus oral antipsychotics (OAs) is not available. The population effectiveness of using these treatments is also not known. OBJECTIVE: To project the effect of using PP1M and PP3M LAIs on psychiatric (Psych) and all-cause (AC) hospitalization rates over 18 months in patients with schizophrenia receiving Medicaid and treated with OAs. METHODS: A decision model, informed by data from 3 randomized controlled trials (PRIDE [NCT01157351], 3001 [NCT00111189], and 3012 [NCT01529515]), was developed to compare 3 strategies: (a) initiating OA and switching only to OA; (b) initiating with PP1M and continuing PP1M if the patient was stable at 6 months (or switching to OA if unstable; PP1M→PP1M); and (c) initiating with PP1M and switching to PP3M if the patient was stable at 6 months (or switching to OA if unstable; PP1M→PP3M). PRIDE data were used to inform the first 6-month outcomes; 3001 and 3012 data were used to inform outcomes in stable patients over the following 12 months. The primary outcome for this decision model study was Psych hospitalizations. AC hospitalizations and time to discontinuation were also assessed. Outcomes from each arm and time portions within an arm were reweighted to reflect the distribution of patient characteristics found in the real-world Medicaid sample with PRIDE trial inclusion/exclusion criteria applied. Several validation exercises were carried out to ensure that the reweighted results could reproduce observed outcomes in the Medicaid sample. RESULTS: Our final target real-world sample size was N=4,609. We found that in the Medicaid sample, compared with initiating treatments with OA, the PP1M→PP1M strategy was projected to produce a per patient decrease of 0.27 (95% CI = -0.43-0.97) and 0.28 (95% CI = -0.28-0.84) in Psych- and AC-related hospitalizations, respectively. Similarly, the PP1M→PP3M strategy was projected to produce a per patient decrease of 0.31 (95% CI = -0.27-0.87) in both Psych- and AC-related hospitalizations over OA. Validation exercises ensured that the reweighting methodology used could replicate observed outcomes in the Medicaid sample. These incremental reductions in hospitalization rates are worth about $3.4-$3.8 billion over an 18-month period in patients with schizophrenia receiving Medicaid. CONCLUSIONS: Our results suggest that using PP1M and PP3M treatment strategies for patients with schizophrenia receiving Medicaid could result in reduced hospitalizations. This finding, along with improvement to patients' health, should be considered when assessing the value of these LAIs. DISCLOSURES: This study was supported by Janssen Scientific Affairs and by unrestricted funds from a consortium of 12 biomedical life sciences companies to the University of Washington. Janssen Scientific Affairs was responsible for the design and conduct of the study; the collection, management, analysis, and interpretation of data; the preparation, review, and approval of the manuscript; and the decision to submit the manuscript for publication. Basu received financial support from Janssen Pharmaceuticals, and his time on this project was also partly covered through unrestricted gift funds from the consortium of biomedical life sciences companies. Benson and Alphs are employees of Janssen Scientific Affairs and are stockholders of Johnson & Johnson. Opinions expressed here do not necessarily reflect those of the University of Washington. This study was presented as a poster at the AMCP Managed Care & Specialty Pharmacy 2017 Annual Meeting; March 27-30, 2017; Denver, CO.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.318
Teacher spread0.300 · 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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Citations11
Published2018
Admission routes1
Has abstractyes

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