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Yannan Li



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    P09 - Health Services Research/Health Economics - Real World Outcomes (ID 121)

    • Event: WCLC 2020
    • Type: Posters
    • Track: Health Services Research/Health Economics
    • Presentations: 1
    • Moderators:
    • Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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      P09.19 - Health Disparities Characteristics in Cancer Survivorships among Sexual Minorities in the US - A Cross-Sectional Study Using BRFSS 2018 Data (ID 3738)

      00:00 - 00:00  |  Presenting Author(s): Yannan Li

      • Abstract
      • Slides

      Introduction

      Lesbian, gay, bisexual, and transgender (LGBT) individuals are estimated to be 3.5% of the US population and have unique healthcare disparities when compared to the general population. Previous studies have shown them with increased smoking prevalence, predisposing this group to higher cancer risks, especially for lung cancer, along with worse cancer survivorships. There were other well-studied risk factors such as poorer mental health and BMI over 25, in association with cancer survival outcomes. Cancer survivors who identified as LGBT individuals also had disparities in accessing healthcare, as they bore more burdens socioeconomically and psychologically. In this study, we aimed to elucidate the health disparities in cancer survivorships among LGBT individuals compared to their non-LGBT counterparts, which will help guide healthcare providers in identifying areas of improvement in relating to barriers to cancer care and explore approaches to improve quality of life.

      Methods

      We conducted a cross-sectional study using the 2018 Behavioral Risk Factor Surveillance System survey data. We used a weighted estimation method for the cancer survivorship model using data from seven states in terms of demographics, health risks, health care access, and cancer survival outcomes. We stratified the data with sexual orientation and gender identity (SOGI) variables to explore potential associations using Chi-Square tests and logistics regression to identify potential health disparities in the LGBT population.

      Results

      Of the 44,348 sample participants in the study, 1439 were self-identified LGBT. About 91.3% of the heterosexual individuals were over 55 years old, whereas 55.9% in transgender individuals (p<0.0001). Half of the transgender individuals described themselves as persons of color (POC), which was significantly higher than 13.8% of such in the heterosexual group. The bisexual group showed the highest smoking rate of 28.9%, which is doubled compared to heterosexual individuals (p<0.0001). The transgender group showed a significant high binge drinking rate of 20.0%, compared to 8.9% in the heterosexual group. In terms of healthcare access, 33.5% of the transgender individuals did not have healthcare insurance coverage, where only 3.4% of gay/lesbian reported so (p<0.0001). Meanwhile, 35% of bisexual individuals reported having 2 or more types of cancer, where the gay/lesbian group only reported 4.3% (p<0.0001). After adjusting for demographic and healthcare access variables, we found that transgender individuals who assigned male at birth were more likely to have uncontrolled pain caused by cancer and its treatments (OR=7.89, 95%CI[5.98, 10.42]), compared to people who were heterosexual and male at birth. Transgender individuals who assigned female at birth were more likely to have poorer mental health (OR=2.47, 95%CI[2.41, 2.53]), compared to people who were heterosexual and female at birth.

      Conclusion

      Health disparities in cancer survivors who identified as LGBT individuals showed different characteristics in each SOGI group. Our result indicated potential worse cancer survival outcomes in this population and revealed the possibility of multiple minority stress with disproportionate race/ethnicity data. Future policymakers should focus on expanding healthcare insurance coverage, promoting physical and mental wellbeing regarding cancer status, re-evaluating cancer pain management approaches, and improving programs for tobacco and alcohol control, to adapt to the needs of the LGBT population.

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    P35 - Pathology - Genomics (ID 105)

    • Event: WCLC 2020
    • Type: Posters
    • Track: Pathology, Molecular Pathology and Diagnostic Biomarkers
    • Presentations: 1
    • Moderators:
    • Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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      P35.09 - Oncogenetic Differences in Never-Smokers versus Smokers with NSCLC Adenocarcinoma Treated at the Mt Sinai Tisch Cancer Institute (ID 3423)

      00:00 - 00:00  |  Author(s): Yannan Li

      • Abstract
      • Slides

      Introduction

      Never-smokers with lung adenocarcinoma (LUAD) have high rates of actionable driver mutations; however, their scope, distribution and clinical utility requires more quantification.

      Methods

      All Mount Sinai patients between 01/01/2015 and 6/01/2020 with a diagnosis of LUAD of any stage with known smoking status who received genetic testing were included. Most patients were analyzed using the Ion or Oncomine hotspot panels or the OCAv3 NGS panel conducted at Sema4. A driver abnormality is defined here as an activating mutation in a signal transduction factor on which the tumor is singularly dependent on for growth and or survival. Drivers were categorized as Tier1: matched with FDA-approved treatment, Tier2: matched with investigational or off-label treatment, and Tier3: non-targetable with current treatments. Patients were considered fully genotyped if they were comprehensively analyzed for alterations in EGFR, KRAS, MET, ALK, RET, ROS1, BRAF, NTRK1-3, ERBB2, NRAS and HRAS, or were considered partially genotyped otherwise.

      Results

      258 never-smokers and 705 smokers were identified as meeting the above criteria. Of the never-smokers, 214 (83%) had a driver mutation with 189 (73%) considered actionable (Tier1 or 2). Within the smoker cohort, 460 (65%) had an identified driver mutation with 305 (43%) actionable (p<0.0001) (Figure 1). When fully and comprehensively sequenced, 95% (73/77) of never-smokers had a driver mutation with 81% (62/77) actionable; whereas, for smokers, 73% (144/197) had a driver with only 50% (99/197) actionable (p<0.0001). Significant differences in the rates and subtypes of EGFR, ALK and KRAS alterations were observed between never-smokers and smokers (Table 1).

      Table 1. Significant differences by smoking (P-values: Fisher's Exact Test)

      Never Smokers (N = 258)

      Smokers (N = 705)

      P-value

      Total EGFR Drivers

      139 (54%)

      120 (17%)

      <0.0001

      Total KRAS Drivers

      32 (12%)

      264 (37%)

      <0.0001

      ALK Fusions

      16 (6.2%)

      11 (1.5%)

      < 0.001

      Any Oncogenic Driver

      214 (83%)

      460 (65%)

      <0.0001

      Any Actionable Driver

      189 (73%)

      305 (43%)

      <0.0001

      Any FDA-indicated Driver

      164 (63%)

      157 (22%)

      <0.0001

      KRAS G12C / All KRAS

      6 / 32 (18%)

      112 / 264 (42%)

      0.012

      EGFR Ex19del / All EGFR

      71 / 139 (51%)

      46 / 120 (38%)

      0.046

      EGFR G719x / All EGFR

      5 / 139 (3.6%)

      19 / 120 (16%)

      < 0.001

      abstract_fig_with_colors.png

      Conclusion

      Actionable driver mutations were frequently observed in both smokers and never-smokers, but were significantly more numerous in never-smokers. Comprehensive NGS revealed driver alterations in 95% of never-smokers. In summary, all efforts should be exhausted to identify or rule out the presence of an actionable driver mutation in LUAD patients requiring systemic treatment.

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