Dataset: Clinical utility and harm potential of direct-to-consumer laboratory test panels — a cross-sectional content analysis

# Dataset: Clinical Utility and Harm Potential of Direct-to-Consumer Laboratory Test Panels ## Overview This dataset accompanies the manuscript: **Agrawal S, Rehan L, Mazur G, Chudek J.** Clinical utility and harm potential of direct-to-consumer laboratory test panels: a cross-sectional content analysis across commercial providers in the United States and Europe. *Clinical Chemistry and Laboratory Medicine* (submitted 2026). **OSF Preregistration:** [https://osf.io/ft2g3/](https://osf.io/ft2g3/) (DOI: 10.17605/OSF.IO/FT2G3) ## Study Description Cross-sectional content analysis of 76 comprehensive wellness panels (≥10 biomarkers) from 12 direct-to-consumer (DTC) laboratory testing platforms across 7 countries (USA, UK, Netherlands, Italy, Finland, Sweden, Poland). Individual tests were classified into a 4-tier clinical utility framework distinguishing beneficial tests (Tier 1), context-dependent tests (Tier 2), low-value waste (Tier 3), and cascade-driving harm (Tier 4). ## Dataset Contents ### 1. Data_Extraction_FINAL_v3.xlsxMaster dataset containing:- **MASTER_EXTRACTION** sheet: 2,829 test-instances across 76 panels from 12 platforms. Columns include platform name, country, package name, price, raw test name (original language), standardized English name, LOINC code, and tier classification.- **UNIQUE_TESTS** sheet: 191 deduplicated unique laboratory analytes with LOINC mappings and platform count.- **PLATFORM_TRACKER** sheet: Platform-level metadata (country, URL, number of panels, extraction date). ### 2. Coding_Guide_v3_0_FINAL.docxStandardized coding guide used by both independent coders. Contains:- Operational definitions for Tiers 1–4- Decision rules for ambiguous cases- Worked examples- PI adjudication precedents ### 3. Data_Extraction_SOP_v2.0.docxStandard operating procedure for data extraction, including:- Platform identification protocol- Test name extraction rules- Composite panel expansion procedure- LOINC mapping workflow- Wayback Machine archiving procedure ### 4. Analysis_Code.pyPython script reproducing all statistical analyses reported in the manuscript:- Tier distribution with Wilson score confidence intervals- Inter-rater reliability (Cohen's κ, linear and quadratic weighted)- Chi-square test across platforms- Expected false-positive calculations- Regional comparisons ### 5. Platform_URLs.csvArchived URLs for all 12 platforms with Wayback Machine snapshot dates and links. ## Methodology - **Extraction period:** Single 7-day window, April 2026- **Standardization:** Multilingual test names → English → LOINC codes- **Classification:** Two independent clinical coders + structured consensus + PI adjudication- **Framework:** 4-tier clinical utility (Tier 1 Beneficial → Tier 4 Harmful/Cascade)- **Guidelines used:** USPSTF, EFLM, ASCO Choosing Wisely, ASCP Choosing Wisely ## Key Results - 191 unique tests identified across 2,829 test-instances- 58.1% of unique tests classified as Tier 3+4 (lacking screening evidence or harmful)- 9 tests classified as Tier 4 (cascade drivers): AFP, CA-125, CA 19-9, CA 15-3, CEA, NSE, D-Dimer, MTHFR, ROMA- Tier 3+4 proportion ranged from 2.8% (Puhti) to 37.9% (Function Health)- Expected false positives per consumer: 1.5 (Synlab Italia) to 9.8 (Randox Health) ## Ethics This study analyzed publicly available commercial data (website content and pricing). No human subjects, patient data, or biological samples were involved. Ethics committee approval was not required. ## Funding European Funds for Lower Silesia 2021–2027 Programme (Priority: European Funds for Entrepreneurial Lower Silesia; Action: Innovative Enterprises), 2024–2026. ## Conflicts of Interest S. Agrawal and L. Rehan are shareholders/employees of Labplus sp. z o.o. (LabTest Checker). J. Chudek and G. Mazur are clinical investigators for LabTest Checker. The product was not used in this study. ## License This dataset is made available under the Creative Commons Attribution 4.0 International License (CC-BY 4.0). ## Citation If you use this dataset, please cite the accompanying manuscript and this Zenodo deposit. ## Note on Supplementary Tables Supplementary Tables S1 (191 test classifications) and S2 (excluded non-laboratory items) are published with the journal article and are not duplicated in this deposit. ## Contact Siddarth Agrawal — [corresponding author email]