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Sonja Kobinger



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    P2.03 - Biology (ID 162)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Biology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.03-04 - The Prognostic Value of Serological Tumor Markers in Lung Cancer – Analysis of 13,373 Cases (ID 800)

      10:15 - 18:15  |  Author(s): Sonja Kobinger

      • Abstract
      • Slides

      Background

      Serological tumor markers such as Carcinoembryonic Antigen (CEA), Cytokeratin 19 Fragments (Cyfra 21-1) and Neuron Specific Enolase (NSE) have been shown to provide prognostic information in lung cancer. We have introduced an algorithm to combine two markers (CEA, Cyfra 21-1) into a new variable the so called tumor marker index (TMI). TMI is defined as the geometric mean of normalized marker values (Muley et al, Anticancer Res 24:1953-56, 2004).

      Method

      We have uploaded available routine tumor marker data from various sources (excel sheets, extracts from laboratory IT-systems and from our clinical cancer registry) into the clinical research data warehouse based on i2b2/tranSMART using Talend Open Studio procedures. We extracted selected clinical parameters together with tumor marker data for further analyses with the statistical software package SPSS 25.0 (IBM Deutschland GmbH, Ehningen). Pretherapeutical tumor markers were measured with Roche Elecsys (Roche Diagnostics GmbH, Penzberg). A complete set of tumor marker data for the calculation of TMI1 (CEA, CYFRA21-1) and TMI2 (CEA, CYFRA21-1, NSE) was available in n=13373 and n=13174 cases, respectively.

      Result

      The median value (range) for TMI1 and TMI2 was found to be 0.94 (0.01-1311.98) and 1.01 (0.01-201.67), respectively. Besides the validation of our originally published prognostic cut off value of 0.54 for TMI1 (Muley et al, Lung Cancer 2008, 60:408-415) in 1315 p-stage I NSCLC patients (figure), we found additional cut off values for the differentiation of prognostic groups in the data set of all patients. Up to 7 groups with patient number >1800 could be significantly differentiated by both indices (table).

      muley_fig_wclc2019.png

      TMI1
      cutoff

      Patients
      (n)

      Median
      (mos)

      HR

      TMI2
      cutoff

      Patients
      (n)

      Median
      (mos)
      HR
      0.42 2,014 62.4 1 0.55 1,989 82.1 1
      0.58 1,837 35.3 1.33 0.70 1,774 40.8 1.39
      0.79 1,891 26.3 1.61 0.89 1,913 23.5 1.92
      1.11 1,913 17.2 2.12 1.15 1,868 16.5 2.49
      1.76 1,916 13.3 2.70 1.64 1,871 13.7 3.09
      3.54 1,891 10.2 3.44 2.73 1,883 9.4 4.34
      >3.54 1,910 6.7 5.00 >2.73 1,871 6.6 5.97

      Conclusion

      The usefulness of our clinical data warehouse for assembling and structuring of clinical parameters and tumor marker data is warranted. The value of TMIs for the stratification of individual risk groups could be verified in one of the world wide largest series of tumor marker data in lung cancer.

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