Molecular Peritoneal Staging for Pancreatic Ductal Adenocarcinoma Using Mutant KRAS Droplet-Digital Polymerase Chain Reaction: Results of a Prospective Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with predilection for peritoneal dissemination. Accurate peritoneal staging is imperative for treatment recommendations, as one-third of patients develop peritoneal recurrence after resection. Because >90% of PDAC tumors harbor mutant KRAS (mKRAS), we sought to determine feasibility of mKRAS DNA detection in peritoneal lavage (PL) fluid using droplet-digital polymerase chain reaction (ddPCR) via a prospective trial. STUDY DESIGN: Patients with nonmetastatic PDAC undergoing staging laparoscopy with PL were included. PL fluid was sent for cytologic examination, CA19-9/CEA levels, and mKRAS ddPCR assay. Clinically positive laparoscopy was defined as gross metastases or positive cytology. PL mKRAS status was compared with gross findings, cytology, and CA19-9/CEA levels. RESULTS: There were 136 patients enrolled; 70 of 136 (51%) patients received neoadjuvant therapy before PL, and 32 of 136 (24%) patients had clinically positive laparoscopy. Cytology was positive in 17 of 136 (13%) patients, and 22 of 136 (16%) patients had gross metastases. Of patients with gross metastases, only 8 of 22 (36%) had positive cytology; 97 of 136 (71%) patients had mKRAS in PL. PL mKRAS was present in 27 of 32 (84%) clinically positive laparoscopies, with higher mean copy number in clinically positive patients (643 vs 10, p = 0.02). Peritoneal mKRAS was positive in an additional 70 clinically negative patients. CONCLUSIONS: This prospective study establishes the feasibility of PL mKRAS detection. Clinically positive disease was identified in 1 in 4 staging laparoscopies. Although PL mKRAS was highly associated with clinically positive findings, many clinically negative laparoscopies had detectable PL mKRAS, suggesting that standard staging may be inadequate. Longer follow-up will elucidate utility of this promising molecular assay.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".