Survival predictors of 177Lu-Dotatate peptide receptor radionuclide therapy (PRRT) in patients with progressive well-differentiated neuroendocrine tumors (NETS)
Bibliographic record
Abstract
Abstract Purpose 177 Lu-Dotatate is an emerging treatment modality for patients with unresectable or metastatic well-differentiated NETs. This study examines survival predictors in patients who received 177 Lu-Dotatate. Methods A retrospective single-center review was conducted, examining 47 individuals with progressive well-differentiated NETs treated with 177 Lu-Dotatate (four induction cycles of 5.5 GBq at 10-week intervals followed by eight maintenance cycles of 3.7 GBq at 6-month intervals). Results Median follow-up was 63.1 months with a median progression-free survival (PFS) of 34.1 months. However, median overall survival (OS) was not reached at the time of analysis. The presence of ≥ 5 bone metastases (hazard ratio HR 4.33; p = 0.015), non-gastroenteropancreatic (non-GEP) NETs (HR 3.22; p = 0.025) and development of interim ascites (HR 3.15; p = 0.047) independently predicted a worse OS. Patients with chromogranin A of ≥ 4 × upper limit of normal (ULN) had shorter OS ( p < 0.001) and PFS ( p = 0.004). Similarly, those with pre-existing ascites demonstrated a worse OS ( p = 0.009) and PFS ( p = 0.026). Liver metastases involving greater than 50% liver volume and the existence of unusual metastatic locations had a negative impact on OS ( p = 0.033) and PFS ( p = 0.026), respectively. Conclusion High burden of skeletal and hepatic metastases, non-GEP-NETs, chromogranin A of ≥ 4 × ULN, unusual metastatic sites, pre-existing and interim ascites are predictors of poor outcomes in patients treated with 177 Lu-Dotatate. These common indicators can be used for the risk stratification and identification of patients most likely to benefit from PRRT. Trial registration ClinicalTrials.gov identifier: NCT02236910, Retrospectively registered on September, 2014.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".