PD19-04 IMPACT OF NOVEL PATIENT-CENTERED PATHOLOGY REPORTS ON MEN UNDERGOING PROSTATE BIOPSY: THE PAPR RANDOMIZED CONTROLLED TRIAL
Bibliographic record
Abstract
You have accessJournal of UrologyProstate Cancer: Detection & Screening II (PD19)1 May 2024PD19-04 IMPACT OF NOVEL PATIENT-CENTERED PATHOLOGY REPORTS ON MEN UNDERGOING PROSTATE BIOPSY: THE PAPR RANDOMIZED CONTROLLED TRIAL Ravi M Kumar, Katherine Lajkosz, Amalia Silberman, Antonio Finelli, Neil Fleshner, Robert Hamilton, Girish Kulkarni, Alexandre Zlotta, Alejandro Berlin, Janet Papadakos, Sangeet Ghai, Dominik Deniffel, David Wiljer, Shabbir Alibhai, Joseph Cafazzo, Masoom Haider, Odelia Lee, Lauren Calicchia, Isabella Janusonis, Mike Lovas, Jayson Kreidstein, Jenna Hiemstra, and Nathan Perlis Ravi M KumarRavi M Kumar , Katherine LajkoszKatherine Lajkosz , Amalia SilbermanAmalia Silberman , Antonio FinelliAntonio Finelli , Neil FleshnerNeil Fleshner , Robert HamiltonRobert Hamilton , Girish KulkarniGirish Kulkarni , Alexandre ZlottaAlexandre Zlotta , Alejandro BerlinAlejandro Berlin , Janet PapadakosJanet Papadakos , Sangeet GhaiSangeet Ghai , Dominik DeniffelDominik Deniffel , David WiljerDavid Wiljer , Shabbir AlibhaiShabbir Alibhai , Joseph CafazzoJoseph Cafazzo , Masoom HaiderMasoom Haider , Odelia LeeOdelia Lee , Lauren CalicchiaLauren Calicchia , Isabella JanusonisIsabella Janusonis , Mike LovasMike Lovas , Jayson KreidsteinJayson Kreidstein , Jenna HiemstraJenna Hiemstra , and Nathan PerlisNathan Perlis View All Author Informationhttps://doi.org/10.1097/01.JU.0001009448.41537.64.04AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Increasingly, patients can access their medical results in real-time through online portals. In prostate cancer care, clinical decisions hinge on biopsy reports. Standard pathology reports (SPRs) use language that can be difficult for patients to understand. In collaboration with patients and experts (surgeons, radiation oncologists, pathologists, health educators, healthcare design engineers and plain language specialists), our group developed patient-centered pathology reports (PAPR) for prostate biopsy. This study assesses whether prostate biopsy PAPRs improves patient experience, understanding, and shared decision-making. METHODS: 63 patients undergoing prostate biopsy were randomized 1:1 to SPR or SPR+PAPR. Individualized PAPRs were sent to patients within 48 hours of the SPR becoming available. Patients completed an investigator designed questionnaire prior to their follow-up encounter, and a validated shared decision-making (SDM-Q-9) and anxiety (STAI-5) questionnaire after the encounter. Differences in continuous variables were assessed using the Mann-Whitney U test; differences in categorical variables were assessed using Fisher's Exact test or Chi-squared test. RESULTS: There were no significant demographic differences at baseline between groups. Most patients were 60-69 years old (55%), had undergraduate education (66%), and were undergoing their first prostate biopsy (45%). More patients receiving SPR+PAPR vs. SPR agreed that their reports were patient friendly (75 vs. 18%, p=0.01), made them feel in control (71 vs. 12%, p=0.01), lowered their anxiety about their prostate condition (86 vs. 9%, p<0.001), and was useful for communicating results to family and friends (82 vs. 45%, p=0.01). Patients in the SPR+PAPR group displayed a greater understanding of their condition (mean of 3.9 vs. 3.2 correct answers; p=0.02) and available treatment options (61% vs. 16%, p<0.001). Mean SDM-Q-9 and STAIS-5 scores were similar between groups; however, more patients receiving PAPRs agreed that their doctor and them reached an agreement on how to proceed after the first follow-up visit (100% vs. 73%, p=0.02). CONCLUSIONS: Receiving individualized, patient-centred pathology reports can improve knowledge and experience for men undergoing prostate biopsy. Download PPT Source of Funding: Dr. Kumar was awarded $50,000 through the Hold'em for life oncology fellowship at the University of Toronto's Temerty Faculty of Medicine and partner hospitals. This value has been matched by the study investigator for the purposes of this study © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e440 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Ravi M Kumar More articles by this author Katherine Lajkosz More articles by this author Amalia Silberman More articles by this author Antonio Finelli More articles by this author Neil Fleshner More articles by this author Robert Hamilton More articles by this author Girish Kulkarni More articles by this author Alexandre Zlotta More articles by this author Alejandro Berlin More articles by this author Janet Papadakos More articles by this author Sangeet Ghai More articles by this author Dominik Deniffel More articles by this author David Wiljer More articles by this author Shabbir Alibhai More articles by this author Joseph Cafazzo More articles by this author Masoom Haider More articles by this author Odelia Lee More articles by this author Lauren Calicchia More articles by this author Isabella Janusonis More articles by this author Mike Lovas More articles by this author Jayson Kreidstein More articles by this author Jenna Hiemstra More articles by this author Nathan Perlis 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 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".