Patient Preferences For Chemotherapy In The Treatment Of Non-Small Cell Lung Cancer: A Multicenter Discrete Choice Experiment (DCE) Study In China.

OBJECTIVE

The study aims to quantify patients' risk-benefit preferences for chemotherapy in the treatment of non-small cell lung cancer (NSCLC), and to elicit their willingness to pay (WTP) for treatment outcomes.

METHODS

A face-to-face discrete choice experiment (DCE) was conducted on NSCLC patients in four tertiary hospitals each from Beijing, Shanghai, Guangzhou and Chengdu in China. Patients were invited to complete choice questions that constructed by seven attributes: progression-free survival (PFS), disease control rate (DCR), rash, nausea and vomiting, tiredness, mode of administration and out-of-pocket costs. A mixed logit model was used to evaluate the choice model. Estimates of relative preferences and marginal willingness to pay for each attribute were then explored.

RESULTS

A total of 361 patients completed the survey. Improvements in PFS (10, 95% CI: 8.4-11.6) were the most important attribute for patients, followed by increase in DCR (4.6, 95% CI: 3.4-5.8). Tiredness (3.9, 95% CI: 2.9-5.1) was judged to be the most important risk. While remaining attributes were ranked in decreasing order of importance: nausea and vomiting (1.9, 95% CI: 0.9-3.0), mode of administration (0.8, 95% CI: 0.2-1.4) and rash (0.5, 95% CI: -0.6-1.5). There was little variation in preferences among patients with different sociodemographic characteristics. Patients were monthly willing to pay $2304 (95% CI, $1916-$2754) that guaranteed 11 months of PFS, followed by $1465 (95% CI, $1163-$1767) per month to improve their disease control rate by 90%.

CONCLUSION

The results suggested that efficacy was the most important attribute for patients. Side effects, mode of administration and treatment cost significantly influenced patient preferences. Patient engagement in prioritizing their treatment preferences should be emphasized during the clinical decision-making process and regimen implementation.