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2026
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| Online Access: | https://doi.org/10.5281/zenodo.19761719 |
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| author | Agrawal, Siddarth Rehan, Leopold Mazur, Grzegorz Chudek, Jerzy |
| author_facet | Agrawal, Siddarth Rehan, Leopold Mazur, Grzegorz Chudek, Jerzy |
| contents | <p># Dataset: Clinical Utility and Harm Potential of Direct-to-Consumer Laboratory Test Panels</p> <p>## Overview</p> <p>This dataset accompanies the manuscript:</p> <p>**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).</p> <p>**OSF Preregistration:** [https://osf.io/ft2g3/](https://osf.io/ft2g3/) (DOI: 10.17605/OSF.IO/FT2G3)</p> <p>## Study Description</p> <p>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).</p> <p>## Dataset Contents</p> <p>### 1. Data_Extraction_FINAL_v3.xlsx<br>Master dataset containing:<br>- **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.<br>- **UNIQUE_TESTS** sheet: 191 deduplicated unique laboratory analytes with LOINC mappings and platform count.<br>- **PLATFORM_TRACKER** sheet: Platform-level metadata (country, URL, number of panels, extraction date).</p> <p>### 2. Coding_Guide_v3_0_FINAL.docx<br>Standardized coding guide used by both independent coders. Contains:<br>- Operational definitions for Tiers 1–4<br>- Decision rules for ambiguous cases<br>- Worked examples<br>- PI adjudication precedents</p> <p>### 3. Data_Extraction_SOP_v2.0.docx<br>Standard operating procedure for data extraction, including:<br>- Platform identification protocol<br>- Test name extraction rules<br>- Composite panel expansion procedure<br>- LOINC mapping workflow<br>- Wayback Machine archiving procedure</p> <p>### 4. Analysis_Code.py<br>Python script reproducing all statistical analyses reported in the manuscript:<br>- Tier distribution with Wilson score confidence intervals<br>- Inter-rater reliability (Cohen's κ, linear and quadratic weighted)<br>- Chi-square test across platforms<br>- Expected false-positive calculations<br>- Regional comparisons</p> <p>### 5. Platform_URLs.csv<br>Archived URLs for all 12 platforms with Wayback Machine snapshot dates and links.</p> <p>## Methodology</p> <p>- **Extraction period:** Single 7-day window, April 2026<br>- **Standardization:** Multilingual test names → English → LOINC codes<br>- **Classification:** Two independent clinical coders + structured consensus + PI adjudication<br>- **Framework:** 4-tier clinical utility (Tier 1 Beneficial → Tier 4 Harmful/Cascade)<br>- **Guidelines used:** USPSTF, EFLM, ASCO Choosing Wisely, ASCP Choosing Wisely</p> <p>## Key Results</p> <p>- 191 unique tests identified across 2,829 test-instances<br>- 58.1% of unique tests classified as Tier 3+4 (lacking screening evidence or harmful)<br>- 9 tests classified as Tier 4 (cascade drivers): AFP, CA-125, CA 19-9, CA 15-3, CEA, NSE, D-Dimer, MTHFR, ROMA<br>- Tier 3+4 proportion ranged from 2.8% (Puhti) to 37.9% (Function Health)<br>- Expected false positives per consumer: 1.5 (Synlab Italia) to 9.8 (Randox Health)</p> <p>## Ethics</p> <p>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.</p> <p>## Funding</p> <p>European Funds for Lower Silesia 2021–2027 Programme (Priority: European Funds for Entrepreneurial Lower Silesia; Action: Innovative Enterprises), 2024–2026.</p> <p>## Conflicts of Interest</p> <p>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.</p> <p>## License</p> <p>This dataset is made available under the Creative Commons Attribution 4.0 International License (CC-BY 4.0).</p> <p>## Citation</p> <p>If you use this dataset, please cite the accompanying manuscript and this Zenodo deposit.</p> <p>## Note on Supplementary Tables</p> <p>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.</p> <p>## Contact</p> <p>Siddarth Agrawal — [corresponding author email]</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19761719 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Dataset: Clinical utility and harm potential of direct-to-consumer laboratory test panels — a cross-sectional content analysis Agrawal, Siddarth Rehan, Leopold Mazur, Grzegorz Chudek, Jerzy direct-to-consumer testing; laboratory medicine; clinical utility; diagnostic cascade; choosing wisely; overdiagnosis; evidence-based screening; DTC testing; LOINC; content analysis; multiplex testing; false positive <p># Dataset: Clinical Utility and Harm Potential of Direct-to-Consumer Laboratory Test Panels</p> <p>## Overview</p> <p>This dataset accompanies the manuscript:</p> <p>**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).</p> <p>**OSF Preregistration:** [https://osf.io/ft2g3/](https://osf.io/ft2g3/) (DOI: 10.17605/OSF.IO/FT2G3)</p> <p>## Study Description</p> <p>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).</p> <p>## Dataset Contents</p> <p>### 1. Data_Extraction_FINAL_v3.xlsx<br>Master dataset containing:<br>- **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.<br>- **UNIQUE_TESTS** sheet: 191 deduplicated unique laboratory analytes with LOINC mappings and platform count.<br>- **PLATFORM_TRACKER** sheet: Platform-level metadata (country, URL, number of panels, extraction date).</p> <p>### 2. Coding_Guide_v3_0_FINAL.docx<br>Standardized coding guide used by both independent coders. Contains:<br>- Operational definitions for Tiers 1–4<br>- Decision rules for ambiguous cases<br>- Worked examples<br>- PI adjudication precedents</p> <p>### 3. Data_Extraction_SOP_v2.0.docx<br>Standard operating procedure for data extraction, including:<br>- Platform identification protocol<br>- Test name extraction rules<br>- Composite panel expansion procedure<br>- LOINC mapping workflow<br>- Wayback Machine archiving procedure</p> <p>### 4. Analysis_Code.py<br>Python script reproducing all statistical analyses reported in the manuscript:<br>- Tier distribution with Wilson score confidence intervals<br>- Inter-rater reliability (Cohen's κ, linear and quadratic weighted)<br>- Chi-square test across platforms<br>- Expected false-positive calculations<br>- Regional comparisons</p> <p>### 5. Platform_URLs.csv<br>Archived URLs for all 12 platforms with Wayback Machine snapshot dates and links.</p> <p>## Methodology</p> <p>- **Extraction period:** Single 7-day window, April 2026<br>- **Standardization:** Multilingual test names → English → LOINC codes<br>- **Classification:** Two independent clinical coders + structured consensus + PI adjudication<br>- **Framework:** 4-tier clinical utility (Tier 1 Beneficial → Tier 4 Harmful/Cascade)<br>- **Guidelines used:** USPSTF, EFLM, ASCO Choosing Wisely, ASCP Choosing Wisely</p> <p>## Key Results</p> <p>- 191 unique tests identified across 2,829 test-instances<br>- 58.1% of unique tests classified as Tier 3+4 (lacking screening evidence or harmful)<br>- 9 tests classified as Tier 4 (cascade drivers): AFP, CA-125, CA 19-9, CA 15-3, CEA, NSE, D-Dimer, MTHFR, ROMA<br>- Tier 3+4 proportion ranged from 2.8% (Puhti) to 37.9% (Function Health)<br>- Expected false positives per consumer: 1.5 (Synlab Italia) to 9.8 (Randox Health)</p> <p>## Ethics</p> <p>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.</p> <p>## Funding</p> <p>European Funds for Lower Silesia 2021–2027 Programme (Priority: European Funds for Entrepreneurial Lower Silesia; Action: Innovative Enterprises), 2024–2026.</p> <p>## Conflicts of Interest</p> <p>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.</p> <p>## License</p> <p>This dataset is made available under the Creative Commons Attribution 4.0 International License (CC-BY 4.0).</p> <p>## Citation</p> <p>If you use this dataset, please cite the accompanying manuscript and this Zenodo deposit.</p> <p>## Note on Supplementary Tables</p> <p>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.</p> <p>## Contact</p> <p>Siddarth Agrawal — [corresponding author email]</p> |
| title | Dataset: Clinical utility and harm potential of direct-to-consumer laboratory test panels — a cross-sectional content analysis |
| topic | direct-to-consumer testing; laboratory medicine; clinical utility; diagnostic cascade; choosing wisely; overdiagnosis; evidence-based screening; DTC testing; LOINC; content analysis; multiplex testing; false positive |
| url | https://doi.org/10.5281/zenodo.19761719 |