Optimizing Tissue Use: A Step-wise Approach to Diagnosing Squamous Cell Lung Carcinoma on Small Biopsies

Background: Histologic subtyping of lung cancer has significant implications for treatment planning. Accurate diagnosis based on cytology/small biopsy specimens is challenging and frequently determined by morphology, as material is often not sufficient for immunohistochemical studies (IHC). We investigated the concordance between the rates of diagnosis from cytology/small biopsies compared with surgical specimens in patients with squamous cell lung cancer (SCC) and the utility of IHC for diagnostic precision in lung cancer subtyping. Methods: We conducted a 5-year retrospective analysis identifying cases of SCC diagnosed on cytology/small biopsies ± IHC and compared them with subsequent surgical specimens when available. The number of patients with SCC on surgical biopsy and the concordance between cytology ± IHC was determined. Results: Over the 5-year period (2011-2015), 231 cases were identified. Surgery was performed on 66 cases (28.5%), of which 87.9% concurred with cytological diagnosis (95% exact binomial confidence interval [CI] = 77.5%-94.6%). There were 36 cases diagnosed in 2014 and 2015 with IHC data. Of those cytology cases with IHC (n = 12), SCC was confirmed by surgery in 91.7% (95% CI = 61.5%-99.8%). Of those without IHC (n = 24), 95.8% were confirmed SCC by surgery (95% CI = 78.9%-99.9%). These rates were not different (Fisher exact test). All cases with IHC were morphologically squamous. Conclusions: Our data demonstrate that diagnostic precision of identifying SCC by cytology/small biopsy is comparable with or without additional IHC studies. We recommend judicious use of IHC on cytology specimens, reserving it for cases where cytomorphology is equivocal. Tissue should be preserved for molecular analysis, which may have therapeutic implications. </jats:sec

Simple parameters to solve a complex issue: predicting response to checkpoint inhibitor therapy in lung cancer

Background: Noninvasive biomarkers predicting immune checkpoint inhibitor (ICI) response are urgently needed. We evaluated the predictive value of pretreatment neutrophil-to-lymphocyte ratio (NLR), smoking history, smoking intensity, BMI and programmed death ligand 1 (PD-L1) expression in non-small-cell lung cancer (NSCLC) patients treated with ICIs. Materials &amp; methods: Single-center retrospective study included 137 patients from July 2015 to February 2018. Outcomes included 3-month disease control rate, progression-free survival, and overall survival. Predictive value of biomarkers was assessed independently and in a multivariable model. Results: NLR was associated with all outcomes. Smoking history was predictive of progression-free survival and smoking intensity was predictive of disease control rate. BMI and PD-L1 were not associated with any outcome. High BMI was associated with low NLR. Conclusion: Simple clinical biomarkers can predict response to ICIs. A score incorporating both clinical factors and established tissue/serum biomarkers may be useful in identifying NSCLC patients who would benefit from ICIs. </jats:p

Predictive value of baseline clinicopathological factors in non-small cell lung cancer (NSCLC) patients on checkpoint inhibitors (CPI).

e14119 Background: Tumor PD-L1 expression and tumor mutational burden currently serve as primary predictive markers for CPI efficacy in NSCLC. However, these markers are imperfect due to tumor heterogeneity, changes over time, and lab variations. These challenges highlight importance of developing dynamic, readily available predictive biomarkers. We evaluated predictive value of pre-treatment Neutrophil-to-Lymphocyte Ratio (NLR), smoking history (SH), body mass index (BMI) and smoking intensity (SI) in NSCLC patients (pts) on CPIs. Methods: Retrospective analysis of NSCLC pts treated with CPIs July 2015 to November 2017. Pt demographics, tumor PD-L1 status positive (pos) or negative (neg) (PD-L1 &gt; 0% or 0% respectively), SH, SI (heavy smokers (HS) or non-heavy smokers (NHS) [ = / &gt; 20 pack-year (PY) and &lt; 20 PY respectively], NLR and BMI high or low based on cutoffs of 5 and 25, respectively were captured. Disease Control Rate (DCR) was defined as objective response or stable disease per RECIST 1.1 at 3 months (m). Median overall survival (OS) and time to progression (TTP) were calculated. Fisher’s exact test and chi-square test were used to compare DCR for each group. Kaplan-Meier curves were used to estimate OS and TTP for each factor. Results: 140 pts were included. NLR was associated with DCR, OS, and TTP. 62/90 (68.9%) pts in the low NLR group and 18/47 (38.3%) in the high NLR group had DCR (p &lt; 0.0006). Median OS for low NLR was 15 m (95% CI: 11.75, 22.25) vs. 5.25 m for high NLR (95% CI: 2.75, 9.75) (p &lt; 0.0005). Median TTP for low NLR was 8 m (95% CI: 6.00, 11.25) vs 3 m for the high (95% CI, 2.00, 4.00) (p &lt; 0.0001). SH was not associated with DCR or survival, but was predictive of TTP. SI was predictive of DCR, but not OS or TTP. 65/100 (65.0%) HS and 15/34 (44.1%) NHS had DCR (p &lt; 0.0320). BMI and PD-L1 (n = 55) were not associated with any outcome. There was association between high BMI and low NLR (P &lt; 0.0381). There were no other associations between factors. Conclusions: NLR &lt; 5 was associated with improvement in all measures of outcome while smoking was associated with some. Neither BMI nor PD-L1 were predictive of any outcome. A score incorporating NLR and smoking status may be beneficial in choosing patients for CPIs. </jats:p