Patient and Clinician Preferences for Genetic and Genomic Testing in Non-Small Cell Lung Cancer: A Discrete Choice Experiment.
Simon J FiferRobyn OrdmanLisa BriggsAndrea CowleyPublished in: Journal of personalized medicine (2022)
Precision (personalised) medicine for non-small cell lung cancer (NSCLC) adopts a molecularly guided approach. Standard-of-care testing in Australia is via sequential single-gene testing which is inefficient and leads to tissue exhaustion. The purpose of this study was to understand preferences around genetic and genomic testing in locally advanced or metastatic NSCLC. A discrete choice experiment (DCE) was conducted in patients with NSCLC ( n = 45) and physicians ( n = 44). Attributes for the DCE were developed based on qualitative interviews, literature reviews and expert opinion. DCE data were modelled using a mixed multinomial logit model (MMNL). The results showed that the most important attribute for patients and clinicians was the likelihood of an actionable test, followed by the cost. Patients significantly preferred tests with a possibility for reporting on germline findings over those without (β = 0.4626) and those that required no further procedures over tests that required re-biopsy (β = 0.5523). Physician preferences were similar (β = 0.2758 and β = 0.857, respectively). Overall, there was a strong preference for genomic tests that have attribute profiles reflective of comprehensive genomic profiling (CGP) and whole exome sequencing (WES)/whole genome sequencing (WGS), irrespective of high costs. Participants preferred tests that provided actionable outcomes, were affordable, timely, and negated the need for additional biopsy.
Keyphrases
- copy number
- small cell lung cancer
- end stage renal disease
- primary care
- ejection fraction
- newly diagnosed
- squamous cell carcinoma
- genome wide
- prognostic factors
- chronic kidney disease
- locally advanced
- advanced non small cell lung cancer
- emergency department
- systematic review
- decision making
- palliative care
- peritoneal dialysis
- gene expression
- computed tomography
- type diabetes
- skeletal muscle
- dna methylation
- patient reported outcomes
- brain metastases
- adipose tissue
- machine learning
- clinical practice
- pain management
- case report
- rectal cancer
- magnetic resonance imaging
- insulin resistance
- dna damage
- health insurance
- data analysis
- weight loss
- big data
- electronic health record
- adverse drug
- patient reported