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Receipt of financial drug assistance for oral targeted therapy among older adults with advanced non-small cell lung cancer (NSCLC).

2023· article· en· W4379281125 on OpenAlexaboutno aff
Anika Kumar, Meera Vimala Ragavan, Sandra Zeng, Melisa L. Wong

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsMedicineGeriatric oncologyCohortLung cancerCancerTargeted therapyInternal medicineFinance

Abstract

fetched live from OpenAlex

e18916 Background: Financial drug assistance programs are a critical resource to mitigate financial toxicity for oral targeted therapy but can be challenging to access and navigate. Older adults with cancer frequently face high copayments for oral targeted therapy, yet they may be less able to navigate assistance programs due to functional and cognitive impairments. To identify potential barriers to receipt of assistance among older adults with advanced NSCLC, we evaluated associations between demographic, clinical, and geriatric assessment characteristics and receipt of financial drug assistance. Methods: We conducted a prospective cohort study at a Comprehensive Cancer Center where thoracic oncology nurses and pharmacists are available to help patients navigate financial drug assistance applications. We enrolled adults age > 65 with advanced NSCLC starting a new chemotherapy, immunotherapy, and/or oral targeted therapy regimen with non-curative intent. For this analysis, we included only older adults who received oral targeted therapy. Patients completed a pretreatment geriatric assessment to evaluate function, cognition, social support, comorbidities, mood, and nutrition. Receipt of financial drug assistance was abstracted from the medical record. We used Fisher’s exact tests to evaluate for differences in demographic, clinical, and geriatric assessment characteristics between those who did and did not receive financial drug assistance. Results: Of the 168 older adults with advanced NSCLC in the parent cohort study, 45 received oral targeted therapy and were included in this analysis. Median age was 74 (range 65-94); 56% were White, 40% Asian, 2% Black, and 2% Hispanic. The majority had Medicare (76%) followed by private insurance (18%), Medicare and Medicaid (4%), and Medicaid alone (2%). On the geriatric assessment, 60% were dependent in instrumental activities of daily living, 20% were dependent in basic activities of daily living, 51% had an abnormal Montreal Cognitive Assessment, and 42% had poor tangible social support. Overall, 9 older adults (20%) received financial drug assistance for their oral targeted therapy. Older adults with a lower household income were more likely to receive financial drug assistance (p = 0.007). There were no statistically significant differences in receipt of financial drug assistance according to other demographic, clinical, or geriatric assessment characteristics including function, cognition, and social support. Conclusions: Older adults with advanced NSCLC on oral targeted therapy with lower household incomes were appropriately more likely to receive financial drug assistance. The lack of associations between receipt of financial drug assistance and function, cognition, and social support suggests that thoracic oncology staff are successfully helping older adults navigate financial drug assistance programs.

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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)0.001
metaresearch head score (Gemma)0.003
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.349
Teacher spread0.303 · 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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Citations0
Published2023
Admission routes1
Has abstractyes

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