Progression-Free Survival Prediction Performance of ChatGPT: Analysis With Real Life Data in Early and Locally Advanced Prostate Cancer.

OBJECTIVE

To evaluate the progression-free survival (PFS) time in patients with early-stage and locally advanced prostate cancer and to compare the estimates provided by ChatGPT with actual survival data.

METHODS

A retrospective analysis was conducted on patients diagnosed with early-stage/locally advanced prostate cancer. Each patient's estimated PFS times were calculated using an artificial intelligence chatbot. These estimates were generated by considering several factors, including the patient's clinical characteristics, tumor stage, treatment modalities, and biochemical parameters. A statistical comparison was conducted between the predicted PFS and actual PFS times.

RESULTS

The AI chatbot tended to overestimate the overall PFS times. A statistically significant discrepancy was observed between the predicted and actual survival times (p < 0.05). A discrepancy of 9.19 months was observed between the PFS predictions made by ChatGPT and the actual PFS. The bias value was 48.57, yet this discrepancy had a negligible impact on clinical practice (Cohen's d = 0.189).

DISCUSSION: Artificial intelligence-based models have the potential to play an important role in the prediction of progression in cancers such as prostate cancer, where 5-10-year survival rates can reach 100%. However, this study's findings indicate that the AI model's predictions are not aligned with the actual clinical data. The reliability of the integration of artificial intelligence into clinical decision support systems can be enhanced through the undertaking of comprehensive future studies.

CONCLUSION

The use of artificial intelligence in predictive modeling may prove an effective approach for forecasting the PFS of prostate cancer. It has the potential to supplant the nomograms that are currently in use. Nevertheless, further studies are required to substantiate the accuracy and reliability of these systems.