IntroductionPre-exposure prophylaxis (PrEP) is highly effective at preventing HIV acquisition, but coverage remains low in high prevalence settings. Initiating and continuing PrEP via online pharmacies is a promising strategy to expand PrEP uptake but little is known about user preferences for this strategy. We describe methods for a discrete choice experiment (DCE) to assess preferences for PrEP delivery from an online pharmacy.Methods and analysisThis cross-sectional study is conducted in Nairobi, Kenya, in partnership with MYDAWA, a private online pharmacy retailer with a planned sample size of >400 participants. Eligibility criteria are: ≥18 years, not known HIV-positive and interested in PrEP. Initial DCE attributes and levels were developed via literature review and stakeholder meetings. We conducted cognitive interviews to assess participant understanding of the DCE survey and refined the design. The final DCE used a D-efficient design and contained four attributes: PrEP eligibility assessment, HIV test type, clinical consultation type and user support options. Participants are presented with eight scenarios consisting of two hypothetical PrEP delivery services. The survey was piloted among 20 participants before being advertised on the MYDAWA website on pages displaying products indicating HIV risk (eg, HIV self-test kits). Interested participants call a study number and those screened eligible meet a research assistant in a convenient location to complete the survey. The DCE will be analysed using a conditional logit model to assess average preferences and mixed logit and latent class models to evaluate preference heterogeneity among subgroups.Ethics and disseminationThis study was approved by the University of Washington Human Research Ethics Committee (STUDY00014011), the Kenya Medical Research Institute, Nairobi County (EOP/NMS/HS/128) and the Scientific and Ethics Review Unit in Kenya (KEMRI/RES/7/3/1). Participation in the DCE is voluntary and subject to completion of an electronic informed consent. Findings will be shared at international conferences and peer-reviewed publications, and via engagement meetings with stakeholders.

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Introduction Biomarker testing is increasingly crucial for patients with early-stage non-small cell lung cancer (eNSCLC). We explored biomarker test utilization and subsequent treatment in eNSCLC patients in the real-world setting. Methods Using COTA’s oncology database, this retrospective observational study included adult patients ≥ 18 years old diagnosed with eNSCLC (disease stage 0–IIIA) between January 1, 2011 and December 31, 2021. Date of first eNSCLC diagnosis was the study index date. We reported testing rates by index year for patients who received any biomarker test within 6 months of eNSCLC diagnosis and by each molecular marker. We also evaluated treatments received among patients receiving the five most common biomarker tests. Results Among the 1031 eNSCLC patients included in the analysis, 764 (74.1%) received ≥ 1 biomarker test within 6 months of eNSCLC diagnosis. Overall, epidermal growth factor receptor ( EGFR ; 64%), anaplastic lymphoma kinase ( ALK ; 60%), programmed death receptor ligand 1 (PD-L1; 48%), ROS proto-oncogene 1 ( ROS1 ; 46%), B-Raf proto-oncogene (40%), mesenchymal epithelial transition factor receptor (35%), Kirsten rat sarcoma viral oncogene (29%), RET proto-oncogene (22%), human epidermal growth factor receptor 2 (21%), and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (20%) were the 10 most frequently tested biomarkers. The proportion of patients undergoing biomarker testing rose from 55.3% in 2011 to 88.1% in 2021. The most common testing methods were Sanger sequencing for EGFR (244, 37%), FISH (fluorescence in situ hybridization) for ALK (464, 75%) and ROS1 (357, 76%), immunohistochemical assay for PD-L1 (450, 90%), and next-generation sequencing testing for other biomarkers. Almost all the 763 patients who received the five most common biomarker tests had a test before the initiation of a systemic treatment. Conclusion This study suggests a high biomarker testing rate among patients with eNSCLC in the US, with testing rates for various biomarkers increasing over the past decade, indicating a continuous trend towards the personalization of treatment decisions.

BACKGROUND Mobile health (mHealth) approaches offer potentially affordable ways to support care of HIV-infected patients in overstretched healthcare systems. However, few studies have analyzed costs associated with mHealth solutions for HIV care. OBJECTIVE This study estimates the total incremental costs and incremental cost per beneficiary of an interactive SMS support intervention within a clinical trial. METHODS The Mobile WAChX trial (NCT02400671) evaluates an interactive semi-automated SMS intervention to improve ART adherence and retention in care among peripartum women in Kenya. Women were randomized to receive one-way vs. two-way SMS. Messages were sent weekly, including motivational and educational content and visit reminders; two-way messaging enabled prompt consultation with nurse as needed. Micro-costing methods were used to collect resource-use related to implementing the Mobile WAChX SMS intervention. At 2 sites (Nairobi and Western Kenya), we conducted semi-structured interviews with health personnel to identify start-up and recurrent activities, obtaining information on personnel, supplies, and equipment. Data on expenditures and prices from project expense reports, administrative records and published government salary data were included to estimate total incremental costs. Using a public provider perspective, we estimated incremental unit costs per beneficiary and per contact during 2017. RESULTS The weighted average annual incremental costs were $3,725 per facility for the two-way messaging group, $62 per beneficiary and $0.85 per contact to reach 115 beneficiaries. For the one-way messaging group, the weighted average annual incremental costs were $2,542 per facility, $42 per beneficiary and $0.66 per contact to reach 117 beneficiaries. The majority of costs were for personnel, 48% in two-way and 33% in one-way messaging groups, respectively. Costs associated with software development and communication accounted for 30% of costs in both intervention arms. CONCLUSIONS Cost information for budgeting and financial planning is relevant for implementing mHealth interventions in national health plans. Given the proportion of costs related to systems development, it is likely that costs per beneficiary will decline with scale-up.