The utility of DR-70, a novel blood biomarker, in the early detection of lung cancer.
Bibliographic record
Abstract
e17521 Background: Lung cancer accounts for the largest percentage of cancer in adults in North America. Non-small cell lung cancer (NSCLC) accounts for 85-90% of all lung cancers with a death rate of 85%. Early diagnosis is the only chance of a cure when surgery or chemo-radiotherapy can be performed. Chest X-ray is the routine first diagnostic step but is not confirmatory. The purpose of this study was to further validate DR-70 utility in lung cancer early detection considering the relatively high sensitivity of this test. Onko-Sure is a regulatory approved blood test for detection/monitoring of lung cancer treatment/recurrence. It measures the accumulation of fibrin/fibrinogen degradation products in the serum using anti-DR-70 antibody. Methods: A total of 239 serum samples were retrospectively obtained from a serum bank and were tested with DR-70. There were two arms: healthy controls (n= 120) and biopsy-confirmed lung cancers (n= 119) including: small cell lung cancer (SCLC) (n=7) and NSCLC (n=112). The NSCLC included adenocarcinoma (n=65), squamous carcinoma (n=37), large cell lung cancer (n=4) and others (n=6). The data were analyzed to find the optimal cut point, sensitivity and specificity of DR-70. Results: The sensitivity and specificity of 63% and 87.5% were achieved, respectively (cut-point of 1.2 ug/ml). For SCLC, the sensitivity and specificity of 57.1% and 82.5% were achieved (cut-point: 1.1 ug/ml). For NSCLC, the sensitivity and specificity of 65.2% and 87.5% were achieved (cut-point: 1.2 ug/ml). Among the subcategories of NSCLC, DR-70 showed the highest sensitivity for acinar cell carcinoma (81.8%). Furthermore, DR-70 showed sensitivity of 59.5%, 70.4, 66.7 and 70% for stages I, II, III, and IV. Conclusions: Chest X-Ray is the routine first step in lung cancer detection with the sensitivity of 78.3%. It is not confirmatory and it can miss lesions smaller than 1 cm. These findings are promising and highlight DR-70 test as an additional first line diagnostic tool that can potentially replace X-ray to increase the diagnosis sensitivity as early as stage I. An enhanced ability to diagnose NSCLC in an early stage (I/II) should significantly improve prognosis, treatment options and survival rate for patients with lung cancer.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".