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S. Jiang



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    P3.04 - Poster Session/ Biology, Pathology, and Molecular Testing (ID 235)

    • Event: WCLC 2015
    • Type: Poster
    • Track: Biology, Pathology, and Molecular Testing
    • Presentations: 1
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      P3.04-080 - Combination of BMI and OLR1 in Prognosis Prediction of Patients with Squamous Non-Small Cell Lung Cancer (ID 604)

      09:30 - 09:30  |  Author(s): S. Jiang

      • Abstract
      • Slides

      Background:
      Lung cancer, especially non-small cell lung cancer (NSCLC), represents enormous challenges in continuously achieving treatment improvements. Besides cancer, obesity is becoming more and more prevalent. Obesity is increasingly recognized as a major risk factor for several types of common cancers. Significant mechanisms overlap in the pathobiology of obesity and tumorigenesis. One of these mechanisms involves oxidized low density lipoprotein receptor 1 (OLR1), as link between obesity and cancer. Additionally, body mass index (BMI) has been widely used in exploiting the role of obesity on a series of diseases, including cancer. Significantly, squamous NSCLC revealed to be divergent clinical and molecular phenotypes compared with non-squamous NSCLC.

      Methods:
      Chart review was performed on 1286 consecutive patients who suffered from squamous NSCLC with between November 2004 and March 2008. 131 of the 1286 patients were enrolled in the final analysis. These 131 patients were randomly assigned (2:1) centrally by computer into training group (n=87) and validation group (n=44). BMI was calculated as follow: BMI (kg/m2) = weight (kg)/height (m2). Surgically resected or biopsied specimens were fixed in formalin and embedded in paraffin for routine histopathological diagnosis and immunohistochemical analysis. Then, PFS was defined as the time from the first documentation to the time of tumor progression or death. The total OLR1 immunostaining score was calculated as the sum of the positively stained tumor cells and staining intensity. OLR1 immunostaining score and BMI were assessed by Fisher’s linear discriminant analysis to discriminate if progression-free survival (PFS) would exceeding 2 years.

      Results:
      The mean follow-up for survivors as of December 2014 was 47.23 months. Mean PFS was 724 days and the overall 1-, 2- and 3-year PFS rates were 87.8%, 47.3% and 39.7%, respectively. OLR1 expressed on tumor cells. There was no significant difference between the training (n=87) and validation (n=44) cohorts (P > 0.1). The clinical classifying model was described by the following equation: Y = -5.811 + 1.285 ×OLR1 immunostaining score + 0.152 ×BMI (eigenvalue 1.272, canonical correlation 0.748, P < 0.001). Group centroids for PFS <= 2 years and PFS > 2 years were 0.914 and - 1.359, respectively. Next, a cut score halfway between the two centroids was determined: cut score= (−1.359 + 0.914)/2 = -0.2225. For the training set of 87 leave-one-out-cross-validated cases, 49 of 52 PFS > 2 years (94.2% sensitivity) and 30 of 35 PFS <= 2 years (85.7% specificity) were correctly classified with an overall accuracy of 90.8% (79 of 87) and an area under the curve (AUC) of 0.938. In the validation set, survival prediction for 40 of the 44 patients (90.9%) with an AUC of 0.979was achieved.

      Conclusion:
      The analysis of combination of BMI and OLR1 could effectively and reproducibly classify patients with squamous NCSLC according to their PFS. Further prospective validation in larger independent cohorts of patients with similar or different regimens is warranted to fully assess its predictive power. However, the combinational model offers a novel tool for survival prediction and could provide a framework for future individualized therapy in patients with squamous NCSLC.

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