A Multicenter Pilot Study Examining the Role of Circulating Tumor Cells as a Blood-Based Tumor Marker in Patients with Extensive Small-Cell Lung Cancer
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Bibliographic record
Abstract
BACKGROUND: Small-cell lung cancer (SCLC), a variant of lung cancer marked by early metastases, accounts for 13% of all lung cancers diagnosed in US. Despite high response rates to treatment, it is an aggressive disease with a median survival of 9-11 months for patients with extensive stage (EX-SCLC). Detection of circulating tumor cells (CTCs) is a novel laboratory technique currently in use to determine response to therapy and to predict prognosis in breast, colorectal, and prostate cancer. We initiated a pilot study to analyze the role of CTCs as a biomarker of response and relapse in patients with EX-SCLC. METHODS: We collected blood samples from chemotherapy naïve patients with EX-SCLC prior to initiation of therapy, after completion of systemic therapy, and follow-up every 6-8 weeks and at relapse. The number of CTCs was determined using the cell search system in a central laboratory. The study was conducted in four different sites, and it was reviewed and approved by respective research review committees and IRBs. RESULTS: We enrolled 26 patients with EX-SCLC, 1 was excluded due to ineligibility, all were treated with platinum and etoposide. We observed partial response in 16 patients, stable disease in 3 patients, 1 patient with disease progression, and 6 patients were not assessed (5 deceased, 1 not available). The overall median number of CTCs in 24 patients measured at baseline and post-tx was 75 (range 0-3430) and 2 (range 0-526), respectively. A significant reduction in CTCs from baseline to post-treatment was identified for 15 subjects; the median reduction was 97.4% (range -100 to +100%, p < 0.001). Higher baseline CTCs and percentage change in post-treatment CTCs were associated with decreased survival. CONCLUSION: We demonstrated that it is feasible to detect CTCs in EX-SCLC. If validated in other prospective studies, CTCs could be a useful biomarker in the management of EX-SCLC by predicting patients' clinical responses to therapy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it