From complexity to clarity: GPT-4 for patient-centered prostate cancer pathology reports

To evaluate whether GPT-4-turbo can generate accurate, patient-centered prostate cancer pathology reports at or below a 6th-grade reading level using a validated reporting template. We retrieved 44 prostate cancer pathology reports from The Cancer Genome Atlas database. We used twenty reports to iteratively refine our prompt refinement and tested the final prompts on 24 unseen reports. GPT-4-turbo generated two patient-centered versions for each report, one below and one above the 6th-grade reading level. We assessed readability using the TextEvaluator tool, which measures eight educational text-complexity dimensions aligned with Common Core standards. We performed paired t-tests to compare the original reports to both simplified versions. GPT-4 significantly reduced the overall text complexity of the pathology reports (p < 0.001). The below 6th-grade versions showed the most improvement. These versions reduced academic vocabulary (mean 68.47 to 23.16), simplified syntactic structures (p = 0.0018), and used more concrete language (36.65 to 44.12). Our iterative prompt engineering eliminated hallucinations and ensured clinical accuracy. GPT-4-turbo, when guided by a well-designed prompt and validated template, can produce accurate, patient-accessible prostate cancer pathology summaries. This approach could improve health communication, particularly for patients with limited health literacy, and offers a low-cost, scalable solution for integrating PCPRs into clinical workflows with minimal burden on clinicians. This workflow may improve patient comprehension of cancer diagnoses, enhance shared decision-making, and promote more equitable access to understandable medical information without substantial additional resource demands. • GPT-4 produced clear patient-friendly prostate cancer reports • Prompt engineering improved readability and accuracy • Reports met 6th-grade reading standards • This method enables scalable, low-cost patient communication

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Publication Details

Journal
Patient Education and Counseling
Published
2026-03-22
DOI
https://doi.org/10.1016/j.pec.2026.109597
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
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article

From complexity to clarity: GPT-4 for patient-centered prostate cancer pathology reports

David Chartash, Soraya Fereydooni, Robert Homer
Patient Education and Counseling
Topic Modeling
article

From complexity to clarity: GPT-4 for patient-centered prostate cancer pathology reports

David Chartash, Soraya Fereydooni, Robert Homer
article en

Abstract

To evaluate whether GPT-4-turbo can generate accurate, patient-centered prostate cancer pathology reports at or below a 6th-grade reading level using a validated reporting template. We retrieved 44 prostate cancer pathology reports from The Cancer Genome Atlas database. We used twenty reports to iteratively refine our prompt refinement and tested the final prompts on 24 unseen reports. GPT-4-turbo generated two patient-centered versions for each report, one below and one above the 6th-grade reading level. We assessed readability using the TextEvaluator tool, which measures eight educational text-complexity dimensions aligned with Common Core standards. We performed paired t-tests to compare the original reports to both simplified versions. GPT-4 significantly reduced the overall text complexity of the pathology reports (p < 0.001). The below 6th-grade versions showed the most improvement. These versions reduced academic vocabulary (mean 68.47 to 23.16), simplified syntactic structures (p = 0.0018), and used more concrete language (36.65 to 44.12). Our iterative prompt engineering eliminated hallucinations and ensured clinical accuracy. GPT-4-turbo, when guided by a well-designed prompt and validated template, can produce accurate, patient-accessible prostate cancer pathology summaries. This approach could improve health communication, particularly for patients with limited health literacy, and offers a low-cost, scalable solution for integrating PCPRs into clinical workflows with minimal burden on clinicians. This workflow may improve patient comprehension of cancer diagnoses, enhance shared decision-making, and promote more equitable access to understandable medical information without substantial additional resource demands. • GPT-4 produced clear patient-friendly prostate cancer reports • Prompt engineering improved readability and accuracy • Reports met 6th-grade reading standards • This method enables scalable, low-cost patient communication

Patient Education and CounselingVol. 149
Quality Education
Openalex Percentile: Top 15%
Topic Modeling
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