Cell therapies - including chimeric antigen receptor T-cell (CAR-T) therapy, tumor-infiltrating lymphocyte (TIL) therapy, T-cell receptor-engineered T-cell (TCR-T) therapy, and natural killer (NK) cell therapy - are emerging treatments for advanced solid tumors. However, their benefit-risk profiles remain uncertain: objective response rates in solid tumors are generally low, treatment-related toxicities such as cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) can be severe, and the manufacturing process is lengthy and costly. Little is known about how physicians and patients weigh these benefits, risks, and burdens when considering cell therapy for advanced solid tumors. This cross-sectional, survey-based observational study will use a discrete choice experiment (DCE) to quantify and compare treatment preferences among approximately 420 oncology physicians and 600 patients with advanced solid tumors in China. Each participant will complete a one-time online questionnaire containing a series of hypothetical treatment choices. The study will estimate the relative importance of key treatment attributes (efficacy, safety, treatment burden, and cost), the maximum acceptable risk that participants are willing to tolerate in exchange for improved efficacy, and differences in preferences between physicians and patients. The findings will inform shared decision-making, cell therapy development, regulatory benefit-risk assessment, and health policy.
This is a cross-sectional, questionnaire-based observational study using a discrete choice experiment (DCE) to elicit treatment preferences from oncology physicians and patients with advanced solid tumors. The study is designed and will be reported in accordance with the ISPOR good research practice guidelines for conjoint analysis. DCE attributes and levels will be developed through a structured process combining a literature review, expert consultation, and cognitive pretesting, and will span the efficacy, safety, treatment burden, and cost domains. A D-optimal fractional factorial design will be used to generate the choice tasks; each participant will be randomly assigned to a block of choice tasks, each presenting pairs of unlabeled hypothetical cell therapy profiles. Preference weights (part-worth utilities) will be estimated using random-parameters logit (mixed logit) models. Secondary analyses will examine the relative importance of attributes, maximum acceptable risk (MAR), marginal willingness to pay (mWTP) where applicable, differences in preferences between physicians and patients, and preference heterogeneity using latent class analysis and interaction-term models. Prespecified sensitivity analyses will be conducted to assess the robustness of the findings.
Study Type
OBSERVATIONAL
Enrollment
1,020
This is an observational study.
The First Affiliated Hospital, Zhejiang University School of Medicine
Hangzhou, Zhejiang, China
RECRUITINGPart-worth utility coefficients (preference weights) for cell therapy benefit-risk attributes
Preference weights (part-worth utility coefficients) for all attribute levels will be estimated using a random-parameters logit (mixed logit) model, fitted separately in the physician and patient cohorts. Each coefficient represents the marginal change in utility associated with moving from the reference level to a given attribute level. The unit of measure is the preference weight, reported with 95% confidence intervals; within an attribute, a higher weight indicates a more preferred level.
Time frame: Day 1
Difference in preference weights for cell therapy benefit-risk attributes between patients and physicians
Between-group differences in preference weights will be evaluated using the Swait-Louviere scale parameter test, a chi-square test of whether the two groups' choice data can be pooled into a single model, accounting for differences in scale (error variance) between groups. The unit of measure is the chi-square test statistic.
Time frame: Day 1
Maximum acceptable risk (MAR) of treatment-related adverse events in exchange for improved efficacy
Maximum acceptable risk (MAR) is the maximum acceptable percentage-point increase in a treatment-related risk that participants are willing to tolerate in exchange for a defined improvement in efficacy. MAR will be calculated from the estimated preference weights as the negative of the ratio between the marginal utility of the efficacy improvement and the marginal disutility of the risk increase from the lowest level of that risk included in the DCE. The unit of measure is percentage points of treatment-related risk.
Time frame: Day 1
Marginal willingness to pay (mWTP) for improvements in cell therapy attributes
Marginal willingness to pay (mWTP) will be calculated as the negative ratio of the preference weight of a non-cost attribute level to the coefficient of the cost attribute. The unit of measure is Chinese yuan (CNY), representing the additional out-of-pocket expense participants are willing to pay for a given attribute level relative to its reference level.
Time frame: Day 1
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