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Background  Targeted treatment with Epidermal Growth Factor Receptor (EGFR) tyrosine kinase inhibitors (TKIs) is superior to systemic chemotherapy in non-small cell lung cancer (NSCLC) patients with  EGFR  gene mutations. Detection of  EGFR  mutations is a challenge in many patients due to the lack of suitable tumour specimens for molecular testing or for other reasons.  EGFR  mutations are more common in female, Asian and never smoking NSCLC patients.    Methods  Patients were from a population-based retrospective cohort of 3556 patients diagnosed with non-squamous non-small cell lung cancer in northern New Zealand between 1 Feb 2010 and 31 July 2017. A total of 1694 patients were tested for  EGFR  mutations, of which information on 1665 patients was available for model development and validation. A multivariable logistic regression model was developed based on 1176 tested patients, and validated in 489 tested patients. Among 1862 patients not tested for  EGFR  mutations, 129 patients were treated with EGFR-TKIs. Their  EGFR  mutation probabilities were calculated using the model, and their duration of benefit and overall survival from the start of EGFR-TKI were compared among the three predicted probability groups: < 0.2, 0.2–0.6, and > 0.6.    Results  The model has three predictors: sex, ethnicity and smoking status, and is presented as a nomogram to calculate  EGFR  mutation probabilities. The model performed well in the validation group (AUC = 0.75). The probability cut-point of 0.2 corresponds 68% sensitivity and 78% specificity. The model predictions were related to outcome in a group of TKI-treated patients with no biopsy testing available ( n  = 129); in subgroups with predicted probabilities of < 0.2, 0.2–0.6, and > 0.6, median overall survival times from starting EGFR-TKI were 4.0, 5.5 and 18.3 months ( p  = 0.02); and median times remaining on EGFR-TKI treatment were 2.0, 4.2, and 14.0 months, respectively ( p  < 0.001).    Conclusion  Our model may assist clinical decision making for patients in whom tissue-based mutation testing is difficult or as a supplement to mutation testing.

bmc cancer

Development and validation of a predictive model for estimating EGFR mutation probabilities in patients with non-squamous non-small cell lung cancer in New Zealand