Advancements in managing pure ductal carcinoma in situ: An 18-year artificial intelligence-aided analysis of 998 patients

• This analysis has included all patients managed for DCIS at the University Hospitals of Strasbourg in France between January 14, 2002 and December 18, 2019 from the prospective SENOMETRY cohort. This study has found: • A stable incidence of DCIS with increase in diagnosis age from 55 to 61 years. • A significant rise in high-grade DCIS cases, particularly DIN3, over 18 years. • Re-excision rates decreasing from 57% in 2002 to 18% in 2019. • AI-driven Onconum software enhanced data extraction and analysis efficiency. • Effective therapeutic de-escalation with reduced margins and fewer axillary surgeries. The integration of artificial intelligence (AI) in oncological diseases has opened new avenues for early cancer detection, accurate risk assessments, and personalized treatment protocols. The objective of our study was to describe the shift in the treatment indications and prognosis of ductal carcinoma in situ (DCIS) in a prospective cohort of 998 patients managed over 18 years at a single University Hospital in France. This analysis included all patients managed for DCIS at the University Hospitals of Strasbourg between January 14, 2002, and December 18, 2019, from the prospective SENOMETRY cohort, which initially included 9599 patients with both in situ and invasive breast cancer. Data were analyzed using Onconum, an AI-based natural language processing tool, to extract structured information from medical records. The incidence of DCIS remained stable at 65 new cases per year. The mean age at diagnosis increased from 55 years in 2002 to 61 years in 2019. There was a significant rise in high-grade DCIS (DIN3) cases from 25% to 35%. The re-excision rate decreased from 57% in 2002 to 18% in 2019. Most DCIS cases were managed with breast-conserving surgeries (682), while total mastectomies accounted for 385 cases. Sentinel lymph node biopsy was performed in 39% of cases, primarily in high-grade and multifocal DCIS. Specific mortality was 0%, with a recurrence rate of 2.2%, predominantly invasive and occurring earlier in high-grade DCIS. Discussion: Over 18 years, there has been a notable shift in the clinicopathological characteristics of DCIS, with an increase in patient age at diagnosis and higher histopathological grades. Therapeutic management evolved significantly, with reduced surgical margins and fewer adjuvant treatments, while maintaining low and stable recurrence rates. AI significantly enhanced data extraction and analysis efficiency, contributing to better clinical decision-making. The study confirms the possibility of therapeutic de-escalation in DCIS, supported by AI-driven data analysis, allowing individualized treatment approaches and leading to optimized patient outcomes.

Authors

Institutions

Publication Details

Journal
Innovative Practice in Breast Health
Published
2024-10-17
DOI
https://doi.org/10.1016/j.ibreh.2024.100022
Primary Topic
Breast Cancer Treatment Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Advancements in managing pure ductal carcinoma in situ: An 18-year artificial intelligence-aided analysis of 998 patients

Antoine Simoulin, Carole Mathelin, Nicolas Thiébaut, Karl Neuberger et al.
Innovative Practice in Breast Health
Breast Cancer Treatment Studies
article

Advancements in managing pure ductal carcinoma in situ: An 18-year artificial intelligence-aided analysis of 998 patients

Antoine Simoulin, Carole Mathelin, Nicolas Thiébaut, Karl Neuberger, Sébastien Molière, Jonathan Sabah, Marie‐Pierre Chenard, Mousselim Gharbi, Charmène Cruchet
article en

Abstract

• This analysis has included all patients managed for DCIS at the University Hospitals of Strasbourg in France between January 14, 2002 and December 18, 2019 from the prospective SENOMETRY cohort. This study has found: • A stable incidence of DCIS with increase in diagnosis age from 55 to 61 years. • A significant rise in high-grade DCIS cases, particularly DIN3, over 18 years. • Re-excision rates decreasing from 57% in 2002 to 18% in 2019. • AI-driven Onconum software enhanced data extraction and analysis efficiency. • Effective therapeutic de-escalation with reduced margins and fewer axillary surgeries. The integration of artificial intelligence (AI) in oncological diseases has opened new avenues for early cancer detection, accurate risk assessments, and personalized treatment protocols. The objective of our study was to describe the shift in the treatment indications and prognosis of ductal carcinoma in situ (DCIS) in a prospective cohort of 998 patients managed over 18 years at a single University Hospital in France. This analysis included all patients managed for DCIS at the University Hospitals of Strasbourg between January 14, 2002, and December 18, 2019, from the prospective SENOMETRY cohort, which initially included 9599 patients with both in situ and invasive breast cancer. Data were analyzed using Onconum, an AI-based natural language processing tool, to extract structured information from medical records. The incidence of DCIS remained stable at 65 new cases per year. The mean age at diagnosis increased from 55 years in 2002 to 61 years in 2019. There was a significant rise in high-grade DCIS (DIN3) cases from 25% to 35%. The re-excision rate decreased from 57% in 2002 to 18% in 2019. Most DCIS cases were managed with breast-conserving surgeries (682), while total mastectomies accounted for 385 cases. Sentinel lymph node biopsy was performed in 39% of cases, primarily in high-grade and multifocal DCIS. Specific mortality was 0%, with a recurrence rate of 2.2%, predominantly invasive and occurring earlier in high-grade DCIS. Discussion: Over 18 years, there has been a notable shift in the clinicopathological characteristics of DCIS, with an increase in patient age at diagnosis and higher histopathological grades. Therapeutic management evolved significantly, with reduced surgical margins and fewer adjuvant treatments, while maintaining low and stable recurrence rates. AI significantly enhanced data extraction and analysis efficiency, contributing to better clinical decision-making. The study confirms the possibility of therapeutic de-escalation in DCIS, supported by AI-driven data analysis, allowing individualized treatment approaches and leading to optimized patient outcomes.

Innovative Practice in Breast HealthVol. 5-6
Centre National de la Recherche Scientifique (FR), Institut de génétique et de biologie moléculaire et cellulaire (FR), Institut de Cancérologie Strasbourg (FR), Hôpital Albert Calmette (FR), Centre Hospitalier de Mulhouse (FR), Hôpitaux Universitaires de Strasbourg (FR), Groupe Hospitalier de la Région de Mulhouse et Sud Alsace (FR), Hôpital Civil, Strasbourg (FR), Université de Strasbourg (FR)
Openalex Percentile: Top 73%
Breast Cancer Treatment Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.