Most patients with advanced non-small cell lung cancer (NSCLC) have a poor prognosis and receive limited benefit from conventional treatments, especially in later lines of therapy. In recent years, several novel therapies have been approved for second- and third-line treatment of advanced NSCLC. In light of these approvals, it is valuable to understand the uptake of these new treatments in routine clinical practice and their impact on patient care. A systematic literature search was conducted in multiple scientific databases to identify observational cohort studies published between January 2010 and March 2017 that described second- or third-line treatment patterns and clinical outcomes in patients with advanced NSCLC. A qualitative data synthesis was performed because a meta-analysis was not possible due to the heterogeneity of the study populations. A total of 12 different study cohorts in 15 articles were identified. In these cohorts, single-agent chemotherapy was the most commonly administered treatment in both the second- and third-line settings. In the 5 studies that described survival from the time of second-line treatment initiation, median overall survival ranged from 4.6 months (95% CI, 3.8–5.7) to 12.8 months (95% CI, 10.7–14.5). There was limited information on the use of biomarker-directed therapy in these patient populations. This systematic literature review offers insights into the adoption of novel therapies into routine clinical practice for second- and third-line treatment of patients with advanced NSCLC. This information provides a valuable real-world context for the impact of recently approved treatments for advanced NSCLC.

Alectinib was associated with prolonged overall survival versus ceritinib, which is consistent with efficacy evidence from clinical trials.

POMRs varied by age group and type of major procedure performed. Collecting surgical data is achievable and can inform future planning and support for national surgical programs. More information is needed on operative outcomes in adults and children in low-resource settings to improve quality and access to care.

Background The efficacy of bevacizumab (BEV) in elderly patients with glioblastoma remains unclear. We evaluated the effect of BEV on survival in this patient population using the Survival, Epidemiology, and End Results (SEER)-Medicare database. Methods This retrospective, cohort study analyzed SEER-Medicare data for patients (aged ≥66 years) diagnosed with glioblastoma from 2006 to 2011. Two cohorts were constructed: one comprised patients who had received BEV (BEV cohort); the other comprised patients who had received any anticancer treatment other than BEV (NBEV cohort). The primary analysis used a multivariate Cox proportional hazards model to compare overall survival in the BEV and NBEV cohorts with initiation of BEV as a time-dependent variable, adjusting for potential confounders (age, gender, Charlson comorbidity index, region, race, radiotherapy after initial surgery, and diagnosis of coronary artery disease). Sensitivity analyses were conducted using landmark survival, propensity score modeling, and the impact of poor Karnofsky Performance Status. Results We identified 2603 patients (BEV, n = 597; NBEV, n = 2006). In the BEV cohort, most patients were Caucasian males and were younger with fewer comorbidities and more initial resections. In the primary analysis, the BEV cohort showed a lower risk of death compared with the NBEV cohort (hazard ratio, 0.80; 95% confidence interval, 0.72–0.89; P < .01). The survival benefit of BEV appeared independent of the number of temozolomide cycles or frontline treatment with radiotherapy and temozolomide. Conclusion BEV exposure was associated with a lower risk of death, providing evidence that there might be a potential benefit of BEV in elderly patients with glioblastoma.

The clinical profiles and outcomes of patients with neurotrophic tropomyosin receptor kinase fusion-positive (NTRK+) solid tumors receiving standard of care other than tropomyosin receptor kinase inhibitor (TRKi) targeted therapy have not been well documented. Here, we describe the clinical characteristics of patients with NTRK+ tumors treated in clinical practice using information from a United States electronic health record-derived clinicogenomic database. We also compared survival outcomes in NTRK+ patients and matched NTRK fusion-negative (NTRK–) patients and investigated the clinical prognostic value of NTRK fusions. NTRK positivity was defined by the presence of a fusion or rearrangement involving NTRK1/2/3, determined using NGS (Foundation Medicine, Inc.). NTRK+ patients (n = 28) were diagnosed with locally advanced/metastatic solid tumors between January 1, 2011 and December 31, 2019 and had received no TRKis (e.g., entrectinib or larotrectinib) during their patient journey. The unselected NTRK−population comprised 24,903 patients, and the matched NTRK−cohort included 280 patients. NTRK+ patients tended to be younger, were more commonly not smokers, and had a shorter time from advanced diagnosis to first NGS report, compared with unselected NTRK−patients; however, these differences were not significant. Median overall survival (OS) from advanced/metastatic diagnosis was 10.2 months (95% CI, 7.2–14.1) for the NTRK+ cohort versus 10.4 months (95% CI, 6.7–14.3) for the matched NTRK−cohort; hazard ratio for death in NTRK+ versus matched NTRK−patients was 1.6 (95% CI, 1.0–2.5; P = 0.05). Genomic co-alterations were rare in the NTRK+ cohort (only two of 28 patients had a co-alteration). Overall, while hazard ratios suggest NTRK fusions may be a negative prognostic factor of survival, there are no significant indications of any favorable impact of NTRK fusions on patient outcomes. TRKis, with their high response rate and good tolerability, are likely to improve outcomes for patients compared with existing standard-of-care treatments.

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Background: Due to the non-randomized nature of real-world data, prognostic factors need to be balanced, which is often done by propensity scores (PSs). This study aimed to investigate whether autoencoders, which are unsupervised deep learning architectures, might be leveraged to compute PS. Methods:We selected patient-level data of 128,368 first-line treated cancer patients from the Flatiron Health EHR-derived de-identified database. We trained an autoencoder architecture to learn a lowerdimensional patient representation, which we used to compute PS. To compare the performance of an autoencoder-based PS with established methods, we performed a simulation study. We assessed the balancing and adjustment performance using standardized mean differences, root mean square errors (RMSE), percent bias, and confidence interval coverage. To illustrate the application of the autoencoder-based PS, we emulated the PRONOUNCE trial by applying the trial's protocol elements within an observational database setting, comparing two chemotherapy regimens.Results: All methods but the manual variable selection approach led to well-balanced cohorts with average standardized mean differences <0.1. LASSO yielded on average the lowest deviation of resulting estimates (RMSE 0.0205) followed by the autoencoder approach (RMSE 0.0248). Altering the hyperparameter setup in sensitivity analysis, the autoencoder approach led to similar results as LASSO (RMSE 0.0203 and 0.0205, respectively). In the case study, all methods provided a similar conclusion with point estimates clustered around the null (e.g., HR autoencoder 1.01 [95% confidence interval = 0.80, 1.27] vs. HR PRONOUNCE 1.07 [0.83, 1.36]). Conclusions: Autoencoder-based PS computation was a feasible approach to control for confounding but did not perform better than some established approaches like LASSO.

2157delG: a frequent mutation in BRCA2 missed by PTT Complete BRCA1 and BRCA2 mutation analysis is a time consuming and expensive process. Many laboratories have chosen to screen only those parts of the genes with a high yield of mutations: exons 2, 11, and 20 in BRCA1 and exons 10 and 11 in BRCA2. While this may be a valid approach in optimising use of scarce resources, it is a somewhat self fulfilling prophesy on the location of most mutations. Furthermore, most institutions use the protein truncation test (PTT) to analyse the large exon 11 in both genes and exon 10 in BRCA2. PTT will not detect missense mutations (possibly a blessing given the diYculty in establishing their eVect), but also mutations at the extreme of each exon will be missed, as they will not produce a recognisably diVerent signal. Our initial strategy has been to screen all exons in both genes to oVer a more complete gene screen, but also to ascertain whether any founder mutation exists in our local population. In BRCA2, we initially analysed 60 samples from aVected subjects in families with four or more breast cancers diagnosed <60 years, and/or families containing male as well as female breast cancer, as well as a subset of 22 breast cancer cases aged <30 years with a family history of breast cancer. We undertook a combined approach of single strand conformation polymorphism (SSCP) for the smaller exons and each end of exons 10 and 11 and PTT of the two large exons. In these initial panels, we detected 15 truncating mutations (25%) of which three (5%) were in segment 11A on SSCP, but were not detected in segment 1 on PTT. On DNA sequencing, these were all found to be the result of a single base deletion (G) at position 2157. All three families contained early onset breast cancer cases with two containing a male breast cancer, one patient being diagnosed at <30 years. A further patient diagnosed aged 32 years with three aVected relatives with breast cancer <40 years of age was sent to Myriad Genetic Laboratories Inc for full gene sequencing. She too was detected as having the 2157delG mutation. While samples from other families have been sent to Myriad, they did not meet the above criteria, although two families with breast and ovarian cancer have had diVerent BRCA2 mutations identified. This high detection rate of 2157delG prompted us to develop a PCR-ARMSTM test to screen a larger set of high risk families. We used this assay to test 46 families with four female breast cancers <60 years and 154 families with three breast cancers <60 years. These families did not contain male breast cancer or ovarian cancer patients. The ARMSTM test detected three further 2157delG mutations which were confirmed on sequencing.The overall detection rate was 1.5% for the sample set, but <8% (0-28%) of these families would be expected to harbour a BRCA2 mutation.1 Our data suggest that 10-20% of BRCA2 mutations in the north west of England will be accounted for by a single mutation. 2157delG has been reported 10 times on the Breast Cancer Information Core dat...