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Record W4226254150 · doi:10.1177/10781552221090199

International society of oncology pharmacy practitioners (ISOPP) position statement: The role of oncology pharmacy practitioners in immunotherapy treatment with immune checkpoint inhibitors for malignant conditions

2022· article· en· W4226254150 on OpenAlexaff
Andrew Walker, Alexandre Chan, Constanza Cortés Labra, Mário L de Lemos, Marc Geirnaert, Elif Aras‐Atik, Jared Borlagdan, Andrea Crespo, Melanie Danilak, Esin Aysel Kandemir, CheaXin Lim, Ramatu Masud Alabelewe, Rina Mutiara, Karunrat Tewthanom, Barbara Yim, Lynne Nakashima

Bibliographic record

VenueJournal of Oncology Pharmacy Practice · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsAlberta Health ServicesCancer Care OntarioCancerCare Manitoba
Fundersnot available
KeywordsMedicinePharmacyOncology nursingPharmacy practiceOncologyClinical pharmacyInternal medicineImmunotherapyPosition statementImmune checkpointCancerFamily medicineNursingNurse education

Abstract

fetched live from OpenAlex

Oncology pharmacists, pharmacy technicians and assistants are key members of the multidisciplinary health care team (MHT) caring for patients receiving immunotherapy with immune checkpoint inhibitors. The International Society of Oncology Pharmacy Practitioners (ISOPP) developed this position statement to provide guidance on the role of oncology pharmacy practitioners in caring for patients receiving immune checkpoint inhibitors.Four key recommendations were identified: 1) participation as an integrated, collaborative member of the MHT;2) provision of education and training for patients, students, residents, fellows and other members of the MHT;3) involvement in clinical governance to optimise the use of immune checkpoint inhibitors and4) involvement in research and development in the field of immunotherapy.In summary, oncology pharmacy practitioners play essential roles within the MHT in caring for patients receiving immune checkpoint inhibitors.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.412
Teacher spread0.375 · 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 designBench or experimental
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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

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