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E. Bedard



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    MA 14 - Diagnostic Radiology, Staging and Screening for Lung Cancer I (ID 672)

    • Event: WCLC 2017
    • Type: Mini Oral
    • Track: Radiology/Staging/Screening
    • Presentations: 1
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      MA 14.03 - Lung Cancer Risk Score Analysis Using Plasma microRNA Profiles (ID 8335)

      15:55 - 16:00  |  Author(s): E. Bedard

      • Abstract
      • Presentation
      • Slides

      Background:
      There is a need for more accurate and minimally invasive methods to screen high risk populations and diagnose lung cancer during its asymptomatic early stages. microRNAs (miRNAs) are small, non-coding strands of RNA that are shown to lead to carcinogenesis when dysregulated. miRNAs, expressed in a tissue specific manner, are stable and detectable in small quantities, thus are promising candidates for biomarkers. Through the use of previous miRNA profiling done in our group, we aim to validate this panel in a large sample size of non-small cell lung cancers (NSCLC) using miRNAs 21, 155, 210, and 223 in blood plasma to determine if this miRNA panel is able to differentiate lung cancer cases from controls.

      Method:
      A nested case-control study of 64 patients with stage I/II NSCLC and 110 healthy controls with similar age, gender, and smoking history was performed. Plasma was provided by Conservant Bio, Lung Cancer Biospecimen Resource Network, and Alberta’s Tomorrow Project. miRNA was isolated using the Qiagen miRNeasy serum/plasma kit. miR-21, 155, 210, and 223 were quantified via RT-PCR using C. elegans miR-39 as a spiked-in endogenous control. Binary logistic regression (SPSS version 15) was performed to develop a combined risk score of the patients’ risk of having lung cancer. Receiver operating curve (ROC) analysis was used to determine risk category cut-off values based on the sensitivity and specificity. Plasma samples were taken 4-7 months post resection and also analyzed and compared to pre-operative samples and controls.

      Result:
      The cases and controls showed similar age ranges (mean=61.97, SD=7.76; mean=61.38, SD=7.95) respectively. Smoking history was higher in the cases (mean=51.5, SD=29.46) than controls (mean=30.98, SD=10.84). The combined score was dichotomized at -0.4169 into high and low risk categories (sensitivity=81%, specificity=41%, AUC=72.3%), the cases pre-operative samples compared to healthy controls was significantly different (odds ratio=3, p-value=0.003, 95% C.I.=[1.440,6.249]). For the cases post-operative samples compared to healthy controls, the combined score was dichotomized at -0.3255 (sensitivity=77%, specificity=41%, AUC=67%), also showing a significant difference (odds ratio=2.3, p-value=0.023, 95% C.I.=[1.120,4.621]). There is no significant difference in the combined risk score when comparing the pre-operative and post-operative NSCLC samples.

      Conclusion:
      Through binary logistic regression miRNA profiling has the potential to assist in screening the high-risk population for lung cancer. Used in conjunction with radiologic screening, this approach could allow early detection and treatment of disease while sparing patients unnecessary investigations and biopsies.

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    P2.13 - Radiology/Staging/Screening (ID 714)

    • Event: WCLC 2017
    • Type: Poster Session with Presenters Present
    • Track: Radiology/Staging/Screening
    • Presentations: 1
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      P2.13-011 - Optimal Selection Criteria for LDCT Lung Cancer Screening (ID 9628)

      09:30 - 09:30  |  Author(s): E. Bedard

      • Abstract

      Background:
      Lung cancer screening programs with low dose computed tomography (LDCT) could be economically viable if they targeted high-risk people. The optimal selection criteria have not been defined in prospective clinical trials. The goal of this prospective study is to test the hypothesis that lung cancer screening based on a highly predictive risk model: The Prostate, Lung, Colon, Ovarian (PLCO~m2012~) is superior to applying National Lung Screening Trial (NLST)-like criteria.

      Method:
      Participants were enrolled through three screening studies, two in Canada (Vancouver and Alberta) and one in London, UK. Eligibility included a PLCOm2012 6-year lung cancer risk ≥1.5% or NLST-like criteria (≥30 pack-years smoking history and quit ≤15 years with some variation in age limits – 55 to 80 years in BC, 55 to 74 in Alberta and 60 to 75 in UCL). The proportion of participants who have been found to have lung cancer or high risk lung nodules, requiring repeat imaging studies or biopsy prior to the next scheduled annual screening were compared between the two selection methods.

      Result:
      The demographics of participants are shown in Table 1. To date, 1,533 received a LDCT, of these, 341 met the PLCOm2012 criteria alone, 169 met NLST-like criteria and 1023 met both criteria. Twenty-seven participants have been found to have lung cancers. All 27 met the PLCOm2012 selection criteria alone while 62% met NLST- like criteria. No lung cancer was found in participants who met NLST-like criteria alone. There are 129 participants with suspicious lung nodules under close surveillance or scheduled for biopsy. Among these, 97% met the PLCOm2012 criteria and 74% met NLST-like criteria.

      Table 1. Clinical and Demographic Features of Study Cohorts
      Study Site British Columbia Alberta London Total
      No. Contacted 802 1661 1990 4453
      No. Eligible 364 741 812 1917
      No. Screened 241 688 604 1533
      Age (yrs) 65+/- 6.3 63.5 +/- 4.2 66+/-4.2 64.8+/- 5.7
      Sex (female/Male) 91F:150M 342F:346M 273F:331M 706M;827M
      Current:Former Smoker 103CS:138Ex 341CS:347Ex 443CS:161Ex 887CS:646Ex
      Pack Years (Mean +/-SD) 47.3+/-22 42.4+/-15.8 47.7+/-22.3 45.3+/-19.8
      Median Follow-up(months) 7.5 9.7 9.7
      No. of lung Cancers 3 7 17 27
      Participants with suspicios nodules 21 41 67 129


      Conclusion:
      Our preliminary results show that fewer people are eligible for screening using NLST-like criteria compare to a highly predictive risk model such as PLCOm2012. Thirty-seven percent more participants with lung cancer are identified by PLCOm2012.