Impact of neuroendocrine tumor diagnosis (NET) on quality of life.
Bibliographic record
Abstract
e18614 Background: With longer median survival for NET patients, the impact of symptoms and treatments on QOL and financial well-being throughout the disease course need to be evaluated to understand the true burden of the disease on patients. Current HRQOL data are during active treatments and this prospective biobank was established to capture this information throughout the disease course. Methods: At Roswell Park Comprehensive Cancer Center, with Institutional Review Board (IRB) approval a NET biobank was established in April 2019 for collecting clinical tissue samples, patient demographics, treatment outcomes, access to care and self-reported HRQoL outcomes. Using previously developed HRQoL questionnaires, we examined the impact of the NET on the quality of life of NET patients and data of 144 patients enrolled to date in the biobank is presented here. Linear regression was used to assess the association of baseline characters with QoL variables. The analysis was done with STATA/IC 16.0. Results: A total of 144 patients are enrolled. Males were 27% (n = 39) and females were 73% (n = 105). The mean age of diagnosis was 54 +/- 0.79, with those between 45 to 65 (72%, n = 103). These patients were enrolled through support groups and social media from 30 different states in the US (135) and 9 pts from Canada. After the diagnosis, 27% of patients had to quit their job. Impact on major HRQoL variables are summarized in Table. Only 21% of patients reported that they feel knowledgeable about NET and got the majority of their support from their primary care (60%) and oncologist (57%). When asked about the most pressing need from their care team, 57% of patients requested their care team had more information about available clinical trials. Sex, age groups did not have statistically significant association on the impact of NETs on the HRQoL of patients. Conclusions: NET diagnosis affects the HRQoL of patients including their social, emotional, and financial well-being. A national biobank capturing data on various demographic, risk factors, treatment sequence, symptoms, HRQoL parameters, financial toxicity is a valuable resource to better understand the needs of this patient group.[Table: see text]
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".