Enregistré dans:
| Auteurs principaux: | , , , , , , , , |
|---|---|
| Format: | Artículo Open Access |
| Publié: |
Wiley
2026
|
| Sujets: | |
| Accès en ligne: | https://onlinelibrary.wiley.com/doi/10.1002/pbc.32086 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1867003151206318080 |
|---|---|
| author | Iyad Sultan Anwar Al‐Nassan Laith Alomari Bayan Altalla Faiha Bazzeh Hadeel Halalsheh Dua'a Zandaki Amal Al‐Omari Asem H. Mansour |
| author_facet | Iyad Sultan Anwar Al‐Nassan Laith Alomari Bayan Altalla Faiha Bazzeh Hadeel Halalsheh Dua'a Zandaki Amal Al‐Omari Asem H. Mansour Iyad Sultan Anwar Al‐Nassan Laith Alomari Bayan Altalla Faiha Bazzeh Hadeel Halalsheh Dua'a Zandaki Amal Al‐Omari Asem H. Mansour |
| collection | Wiley Open Access |
| contents | Development and Validation of an Automated Pediatric Cancer Staging Calculator Using the Toronto Pediatric Cancer Stage Guidelines Iyad Sultan Anwar Al‐Nassan Laith Alomari Bayan Altalla Faiha Bazzeh Hadeel Halalsheh Dua'a Zandaki Amal Al‐Omari Asem H. Mansour Pediatric Blood & Cancer ABSTRACT Background Pediatric cancer stage at diagnosis is critical for prognosis and research comparisons. The Toronto Pediatric Cancer Stage Guidelines standardize staging across childhood malignancies. We developed a framework for automated staging of pediatric cancers using electronic health records. Methods An extraction pipeline was implemented to orchestrate agents. The system ingests notes from the first 3 months after diagnosis. Agents select the most appropriate staging schema based on diagnosis, calculate the stage, and then validate its accuracy. We tested the tool on 500 pediatric patients from our institutional registry. Cases outside the Toronto schema were excluded, yielding 433 evaluable cases. Each case was processed independently in two runs. The outputs were compared to an expert consensus reference stage (ground truth) established by four pediatric oncologists. Results The automated system matched the reference stage in 91.2% of cases overall. Per‐run accuracy (compared to ground truth) was 93.8% for the first run and 88.7% for the second run. The two runs agreed on 89.8% of cases (Cohen's κ = 0.785, p < 0.001). Accuracy dropped significantly when the validation agent failed the first attempt and requested a recalculation. For stages obtained from the first attempt, accuracy was 97%; while for stages achieved on subsequent attempts, accuracy was 77%. Conclusion We demonstrate the first automated staging system for pediatric cancers using standardized Toronto criteria. The tool showed high accuracy comparable to human experts and excellent consistency between independent runs. We propose a hybrid workflow that flags uncertain cases for human review, yielding approximately 97% accuracy with approximately 30% human adjudication. 10.1002/pbc.32086 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| doi_str_mv | 10.1002/pbc.32086 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_pbc_32086 |
| institution | Wiley Open Access |
| license_str_mv | http://onlinelibrary.wiley.com/termsAndConditions#vor |
| publishDate | 2026 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Development and Validation of an Automated Pediatric Cancer Staging Calculator Using the Toronto Pediatric Cancer Stage Guidelines Iyad Sultan Anwar Al‐Nassan Laith Alomari Bayan Altalla Faiha Bazzeh Hadeel Halalsheh Dua'a Zandaki Amal Al‐Omari Asem H. Mansour Pediatric Blood & Cancer Development and Validation of an Automated Pediatric Cancer Staging Calculator Using the Toronto Pediatric Cancer Stage Guidelines Iyad Sultan Anwar Al‐Nassan Laith Alomari Bayan Altalla Faiha Bazzeh Hadeel Halalsheh Dua'a Zandaki Amal Al‐Omari Asem H. Mansour Pediatric Blood & Cancer ABSTRACT Background Pediatric cancer stage at diagnosis is critical for prognosis and research comparisons. The Toronto Pediatric Cancer Stage Guidelines standardize staging across childhood malignancies. We developed a framework for automated staging of pediatric cancers using electronic health records. Methods An extraction pipeline was implemented to orchestrate agents. The system ingests notes from the first 3 months after diagnosis. Agents select the most appropriate staging schema based on diagnosis, calculate the stage, and then validate its accuracy. We tested the tool on 500 pediatric patients from our institutional registry. Cases outside the Toronto schema were excluded, yielding 433 evaluable cases. Each case was processed independently in two runs. The outputs were compared to an expert consensus reference stage (ground truth) established by four pediatric oncologists. Results The automated system matched the reference stage in 91.2% of cases overall. Per‐run accuracy (compared to ground truth) was 93.8% for the first run and 88.7% for the second run. The two runs agreed on 89.8% of cases (Cohen's κ = 0.785, p < 0.001). Accuracy dropped significantly when the validation agent failed the first attempt and requested a recalculation. For stages obtained from the first attempt, accuracy was 97%; while for stages achieved on subsequent attempts, accuracy was 77%. Conclusion We demonstrate the first automated staging system for pediatric cancers using standardized Toronto criteria. The tool showed high accuracy comparable to human experts and excellent consistency between independent runs. We propose a hybrid workflow that flags uncertain cases for human review, yielding approximately 97% accuracy with approximately 30% human adjudication. 10.1002/pbc.32086 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| title | Development and Validation of an Automated Pediatric Cancer Staging Calculator Using the Toronto Pediatric Cancer Stage Guidelines |
| topic | Pediatric Blood & Cancer |
| url | https://onlinelibrary.wiley.com/doi/10.1002/pbc.32086 |