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<p>In prostate cancer centers, treatment and progression data are documented both at the center and in the state cancer registry (oBDS). A&#xa0;high degree of consistency is essential for registry reflection, quality assurance, and research. OncoBox Compare was developed to highlight discrepancies between registry and center data in a&#xa0;structured manner and to clarify them jointly. In a&#xa0;multicenter pilot and expansion project (key figures for 2019/2022), the OncoBox Compare web application was implemented in three cancer registries and seven prostate cancer centers. Both partners exported quality-checked XML data sets (OncoBox Prostate) and compared (1)&#xa0;collective consistency and (2)&#xa0;predefined data fields (including TNM status, Gleason score, and treatment methods) on a&#xa0;case- and field-based basis; responses and clarifications were documented in the application. For primary cases, a&#xa0;concordance rate of &gt; 95% was achieved for the collective, thus demonstrating the feasibility of joint data reconciliation. Lower concordance rates were observed for center cases with recurrence or (secondary) distant metastasis, due to differences in interpretation, reporting times, and cross-year assignments. At the field level, structural deviations occurred primarily in TNM status (e.g., selection of the relevant T&#xa0;status for multiple stages, NX/MX) as well as in Gleason score and watchful waiting strategies/active surveillance (AS/WW); incomplete reports from the outpatient sector also had an impact. OncoBox Compare supports registries and centers in the systematic analysis of data quality and the reflection of specific correction and harmonization steps. The results show high stability for primary cases, while clear rules on case definition and time logic are required for complex courses. The procedure is suitable as a&#xa0;scalable building block for improving data quality and for more robust use of cancer registry data.</p>

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OncoBox Compare – Eine innovative Webanwendung erhöht die Datenvergleichbarkeit zwischen Krebsregistern und onkologischen Zentren

  • 期刊论文

  • 发表日期：

    2026年5月4日

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  • Katharina Weinert,
  • Ruben Hamann,
  • Christian Behr,
  • Dirk Bohn,
  • Carolin Kuhl,
  • Frank Kauff,
  • Elke Burger,
  • Wolfgang Blau,
  • Florian Ohliger,
  • Gerson Lüdecke,
  • Martin Middeke,
  • Julia Schittko,
  • Vanessa Kolb,
  • Sebastian Dieng,
  • Philipp Kachel

摘要

In prostate cancer centers, treatment and progression data are documented both at the center and in the state cancer registry (oBDS). A high degree of consistency is essential for registry reflection, quality assurance, and research. OncoBox Compare was developed to highlight discrepancies between registry and center data in a structured manner and to clarify them jointly. In a multicenter pilot and expansion project (key figures for 2019/2022), the OncoBox Compare web application was implemented in three cancer registries and seven prostate cancer centers. Both partners exported quality-checked XML data sets (OncoBox Prostate) and compared (1) collective consistency and (2) predefined data fields (including TNM status, Gleason score, and treatment methods) on a case- and field-based basis; responses and clarifications were documented in the application. For primary cases, a concordance rate of > 95% was achieved for the collective, thus demonstrating the feasibility of joint data reconciliation. Lower concordance rates were observed for center cases with recurrence or (secondary) distant metastasis, due to differences in interpretation, reporting times, and cross-year assignments. At the field level, structural deviations occurred primarily in TNM status (e.g., selection of the relevant T status for multiple stages, NX/MX) as well as in Gleason score and watchful waiting strategies/active surveillance (AS/WW); incomplete reports from the outpatient sector also had an impact. OncoBox Compare supports registries and centers in the systematic analysis of data quality and the reflection of specific correction and harmonization steps. The results show high stability for primary cases, while clear rules on case definition and time logic are required for complex courses. The procedure is suitable as a scalable building block for improving data quality and for more robust use of cancer registry data.