MP33-06 EXPERIENCE OF THE VIRTUAL CANADIAN TESTICULAR CANCER SECOND OPINION GROUP
Bibliographic record
Abstract
You have accessJournal of UrologyCME1 Apr 2023MP33-06 EXPERIENCE OF THE VIRTUAL CANADIAN TESTICULAR CANCER SECOND OPINION GROUP J Jesus Cendejas-Gomez, Robert James Hamilton, Michel Jewett, Victor Sandoval, and Nicholas Edgar Power J Jesus Cendejas-GomezJ Jesus Cendejas-Gomez More articles by this author , Robert James HamiltonRobert James Hamilton More articles by this author , Michel JewettMichel Jewett More articles by this author , Victor SandovalVictor Sandoval More articles by this author , and Nicholas Edgar PowerNicholas Edgar Power More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003266.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Testicular cancer (TC) is the most frequent solid neoplasia in male patients between 15-35 years. The cases complexity increases in the metastatic stages and the implementation of evidence into the practice is more difficult. Second-opinion groups have shown their utility in improving the implementation of evidence-based treatments. Our main objective is to analyze the utility of a second opinion group in changing decision-making in patients with TC in Canada. As secondary objectives, we will analyze the number of answers per question, the average waiting time for second opinions, the different types of questions, and the over and undertreatment. METHODS: This is a retrospective analysis of 132 cases from the virtual Canadian testicular cancer second opinion group. The discussion of cases was carried out anonymously on the Google groups platform, in which doctors from 9 different provinces and different centers throughout Canada participate, including oncologists, urologist oncologists, and radiotherapists. Collected data include patients' demographic, histological, and treatment data. From the medical standpoint the number of answers, type of question, measured concordance between first and second opinions, and finally change in treatments after the discussion. The information was analyzed from June 2014 to July 2022. RESULTS: We included 132 cases of patients with testicular tumors and extragonadal primary germ cell tumors (GCT) in Canada.The most common histology was GCT in 94% (124/132), non-seminomas represented 72.7% (96/ 124). The most common clinical stage was metastatic in 94.7%.The mean of second opinions was 4.7, the 81% of seekers got responses from at least 3 different centers, and 56.8% of questions received a response from at least two different specialties. The average waiting time for the total of second opinions was less than 1 day. The questions come from academic centers in 81%, and the most common seeker doctors were the oncologists with 86.4% of the questions. The most frequent kind of question was related to chemotherapy in 49%.Comparing the first and second opinions, we found 24% of overtreatment and 26% of undertreatment, with a surprising 52% of potentially changing decision-making. In the multivariable analysis we did not find statistically significant predictors for changing decision-making. CONCLUSIONS: A virtual second opinion group could be a very valuable and easily accessible tool to improve the treatment of patients with complex testicular cancers, with an important percentage of potential changes in treatment even in academic cancer centers. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e452 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information J Jesus Cendejas-Gomez More articles by this author Robert James Hamilton More articles by this author Michel Jewett More articles by this author Victor Sandoval More articles by this author Nicholas Edgar Power More articles by this author Expand All Advertisement PDF downloadLoading ...
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.175 | 0.019 |
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".