Abstract 65: Point of Care Urine Metabolomics Test to Diagnose Colorectal Cancers in Low- and Middle-Income Countries: A Pilot Controlled Trial in Southwestern Nigeria
Bibliographic record
Abstract
Abstract Purpose: The incidence of colorectal cancer (CRC) is increasing in LMICs, with patients experiencing poorer outcomes compared to HICs due mainly to lack of screening and late diagnosis. A cost-effective early diagnosis test for CRC could allow earlier-stage diagnosis with better outcomes and may also prevent patients from developing CRC, however such a test is not yet available in Nigeria and other LMICs. This study piloted a Point of Care (POC) real-time urine metabolomics test, to evaluate its validity in diagnosing CRC among at-risk patients and assess the willingness of patients in Southwestern Nigeria to utilize and pay for the test. Methods: A pilot-controlled trial was carried out among 72 patients (34 cases, 38 controls) in southwestern Nigeria. The cases had histopathological diagnosis of CRC while controls were at-risk adults. The POC biosensor uses a disposable chip and can be connected to a smart device using Bluetooth. It reports if the patient’s urine contained metabolites consistent with CRC. We assessed validity of the test using sensitivity, specificity, positive predictive and negative predictive values. We pre- specified a specificity of 50% with a goal of ≥ 80% sensitivity to estimate the potential of the test to half the referrals to colonoscopy. Utilizing structured questionnaires, we assessed perception towards the test and willingness to uptake the urine test. Results: The mean age for cases and controls were 57.06 ± 16.06 and 54.84 ± 13.05 respectively. The overall sensitivity, specificity, positive predictive and negative predictive values for all respondents were 91.18%, 81.58%, 81.58% and 91.18% respectively, with an area under the ROC curve of 0.86. With specificity fixed at 50%, overall sensitivity for all respondents was 94.5%, and all stratifications had sensitivity >90%, with the stratification for those with hemorrhoids/anal fissure, hemorrhoids/anal fissure + bloody stool and hemorrhoids/anal fissure + bloody stool + weight loss having a sensitivity of 100%. Overall, 70 (98.6%) were satisfied with the urine-based CRC screening, and respondents were willing to pay a mean amount of 8,008.20 Naira (about $5.2) for the test. Conclusion: We developed and pilot tested a urine metabolite early diagnosis POC test that met our pre- determined criteria for success and had high acceptance rates among Nigerian patients. We are planning a much larger multi-institutional implementation trial to determine if these results can scale up. Citation Format: Adeleye Abiodun Adeomi, Olusegun Alatise, David Wishart, Scott MacKay, Olalekan Olasehinde, Funmilola Wuraola, Adewale Adisa, Tajudeen Mohammed, Adewale Aderounmu, Omolade Adefolabi Betiku, Oluwatosin Zainab Omoyiola, Adeoluwa Oluwaseyi Adeleye, Samson Oluwagbemiga Ogunleye, Olusegun Joshua Babatunde, Oluwabusayomi Roseline Ademakinwa, Israel Adeyemi Owoade, Jacob Mobolaji, Cristina Olcese, Rivka Kahn, Naqiya Rahil Choonawala, Grace Fitzgerald, H. Dean Hosgood, T. Peter Kingham. Point of Care Urine Metabolomics Test to Diagnose Colorectal Cancers in Low- and Middle-Income Countries: A Pilot Controlled Trial in Southwestern Nigeria [abstract]. In: Proceedings of the 13th Annual Symposium on Global Cancer Research; 2025 Sep 16. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(12_Suppl):Abstract nr 65.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".