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Xiaofei Wang



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    OA13 - Ideal Approach to Lung Resection and Novel Perioperative Therapy (ID 146)

    • Event: WCLC 2019
    • Type: Oral Session
    • Track: Treatment of Early Stage/Localized Disease
    • Presentations: 1
    • Now Available
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      OA13.01 - SPECS2 Lung Cancer Consortium Prospective Multicenter Validation of Prognostic Signature for Early Stage Squamous Lung Cancer (Now Available) (ID 2723)

      11:30 - 13:00  |  Author(s): Xiaofei Wang

      • Abstract
      • Presentation
      • Slides

      Background

      Squamous Lung Cancer (SC) which constitutes 30% of all non-small cell lung cancers (NSCLC) has few targeted therapy options for advanced disease. Surgery for early SC is the best treatment strategy; however, even patients who undergo surgery for stage IA or IB disease are still at a substantial risk for recurrence and death. Adjuvant therapy is not currently indicated for stage I SC smaller than 4 cm. Prior reports suggest gene expression-based signatures that may predict recurrence in patients with stage I SC, but none has been validated or is in clinical use. The SPECS2 Lung Cancer Consortium was assembled to compare and attempt to validate previously published prognostic signature(s) according to the guidelines proposed by Subramanian and Simon (J Natl Cancer Inst 2010; 7:327).

      Method

      The multi-institutional team assembled 249 frozen SC samples representing six participating institutions (cohort 1). These samples were fully annotated in a redcap database hosted by the independent statistical core. Cohort 2 was assembled utilizing 234 frozen SC samples from a prospective multi-institutional NCTN lung biobanking protocol (NCT00899782). RNA was extracted and profiled with U133A microarrays (Affymetrix) in independent core facilities. The data was transferred directly to the SPECS2 Lung statistical core in collaboration with the Alliance Statistical core and the performance of 6 most promising candidate signatures was evaluated relative to a base model that included only age, gender and AJCC stage (editions 6, 7, 8).

      Result

      Analysis of Cohort 1 demonstrated that only one signature (Raponi et al, Cancer Res 2006; 66:7466) significantly enhanced prognosis relative to the base model, independent of AJCC edition. This was also observed in Cohort 2, where Uno’s C index associated with AJCC 8th edition stage, sex and age (0.561; 0.468-0.654) was significantly (p <0.05) increased when the prognostic signature was added to the model (0.683; 0.611-0.755).

      Conclusion

      The SPECS2 Lung Cancer Consortium was successful in validating a previously published prognostic molecular signature for early stage SC using rigorous experimental design. To our knowledge, this is the first unbiased validation of a lung cancer prognostic signature using multi-institutional prospective specimens. These results support a clinical trial designed to evaluate the potential role of adjuvant therapy in completely resected early stage SC.

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    P1.17 - Treatment of Early Stage/Localized Disease (ID 188)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Treatment of Early Stage/Localized Disease
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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      P1.17-11 - Nomogram Predicting Overall Survival Benefit of Stereotactic Ablative Radiotherapy for Early Stage Non-Small Cell Lung Cancer (ID 940)

      09:45 - 18:00  |  Author(s): Xiaofei Wang

      • Abstract
      • Slides

      Background

      Stereotactic ablative radiotherapy (SABR) is the preferred treatment for medically inoperable T1-T2N0M0 non-small cell lung cancer (NSCLC). This population is at high risk of mortality from comorbidities precluding surgery. A nomogram to better identify patients most likely to benefit from SABR would be clinically meaningful.

      Method

      Adults with T1-T2N0M0 NCSLC (AJCC 7th edition) treated with SABR (30-70 Gy in 1-10 fractions with biologically effective dose ≥100 Gy10) or observation between 2004-2015 in the National Cancer Database were identified. Exclusion criteria included prior malignancy, surgery to the primary tumor, chemotherapy, and no pathologic diagnosis. Propensity score was used to match SABR and observation cohorts on prognostic demographic and clinicopathologic factors identified by logistic regression. Using backward selection, a multivariable Cox proportional hazards model with Frailty term was identified predicting 2- and 5-year overall survival (OS) via a nomogram. The model prediction accuracy was assessed by the concordance between observed and predicted OS.

      Result

      4,440 matched pairs (total n=8,880) were identified with median age 75, 53% female, 54% Charlson-Deyo comorbidity index of zero, 62% tumor size ≤3 cm, and 50% adenocarcinoma. Factors associated with improved OS on multivariable analysis included younger age (HR 0.824 by decade, p<0.001), female sex (HR 0.809, p<0.001), lower comorbidity index (HR 0.647 for 0 versus ≥3, p<0.001), smaller tumor size (HR 0.595 for ≤3cm versus 5.1-7cm, p<0.001), adenocarcinoma histology (p<0.001), and SABR (p<0.001). Interaction between SABR and histology was significantly associated with OS (p=0.017). Uno’s concordance index, evaluating the nomogram’s accuracy for predicting OS, was 0.623 (95%CI 0.615–0.631) based on 100 perturbations.

      nomogram.jpg

      Conclusion

      This nomogram predicts the impact of SABR versus observation on 2- and 5-year OS, and may help identify patients with medically inoperable T1-T2N0M0 NSCLC who would benefit most from SABR. Inclusion of other variables, such as performance status, may improve the model prediction accuracy.

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