Time from immune checkpoint inhibitor to sotorasib use correlates with risk of hepatotoxicity in non-small cell lung cancer: A brief report.

INTRODUCTION: We evaluated the risk factors and outcomes for patients who experienced hepatotoxicity after use of sotorasib in KRAS G12C mutated NSCLC. METHODS: Retrospective review of medical records of patients with KRAS G12C mutated NSCLC who received sotorasib between May 28th, 2021, and December 31st, 2021 across all Mayo Clinic sites, with follow up until December 31st, 2022. RESULTS: Thirty-one patients received sotorasib as standard of care treatment. Grade 3 or higher hepatoxicity was seen in 32% (10/31) patients presenting at a median of 51 days (range, 27-123) of sotorasib initiation. Baseline demographics were comparable between patients with and without ≥grade 3 hepatotoxicity, except for presence of CNS metastases and time from prior immune checkpoint inhibitor (ICI) treatment. Improvement in liver tests was observed in all patients after stopping sotorasib, and it was restarted at a lower dose in 8 patients. Despite dose reduction, hepatotoxicity requiring sotorasib discontinuation occurred in 2 patients. Twenty-eight of 31 patients had received prior ICI. Median time from prior ICI therapy was 69 days (range, 4-542). Rates of ≥grade 3 hepatoxicity were 75% (3/4), 64% (7/11) and 0% (0/13) for patients who received ICI within 30 days, 31-90 days and >90 days. None of the 3 patients without prior ICI exposure developed hepatoxicity. The median PFS and OS were 3.9 months and 9.9 months respectively. CONCLUSION: One-third of patients developed grade 3 or higher sotorasib induced hepatotoxicity. Risk of hepatotoxicity was higher in patients who received sotorasib within 90 days of ICI treatment.

Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology.

A model's ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are deployed into real-world medical settings. In the domain of cancer digital histopathology, we describe a clinically-oriented approach to uncertainty quantification for whole-slide images, estimating uncertainty using dropout and calculating thresholds on training data to establish cutoffs for low- and high-confidence predictions. We train models to identify lung adenocarcinoma vs. squamous cell carcinoma and show that high-confidence predictions outperform predictions without uncertainty, in both cross-validation and testing on two large external datasets spanning multiple institutions. Our testing strategy closely approximates real-world application, with predictions generated on unsupervised, unannotated slides using predetermined thresholds. Furthermore, we show that uncertainty thresholding remains reliable in the setting of domain shift, with accurate high-confidence predictions of adenocarcinoma vs. squamous cell carcinoma for out-of-distribution, non-lung cancer cohorts.

Correlation of Somatostatin Receptor 2 Expression, 68Ga-DOTATATE PET Scan and Octreotide Treatment in Thymic Epithelial Tumors.

Somatostatin receptor 2 (SSTR2) has been shown to be expressed in a subset of neuroendocrine tumors and carcinomas and plays a role in imaging studies and guiding therapy. Patients with tumors expressing SSTR2 may be successfully treated with somatostatin inhibitors or radiolabeled somatostatin analogues. We studied SSTR2 expression in TET and correlated it with 68Ga-DOTATATE PET/CT or 68Ga-DOTATATE PET/MR results and treatment outcome. An institutional database of TET was searched for thymoma, thymic carcinoma, and thymic neuroendocrine tumor (TNET) with available resection specimens. Cases were subtyped (2021 WHO classification) and staged (8th AJCC/UICC staging). A section was stained with anti-SSTR2 antibody (clone UMB1). Percent tumor cells with membranous staining was recorded if present in ≥1% of tumor cells. Medical records were searched for 68Ga-DOTATATE PET scans and treatment. Statistical analysis was performed. Eighty patients (1969-2021) with a median age of 61.3 years (range, 19.1-87.3) (37 males, 46.3%) had thymic carcinoma (N=33), TNET (N=7), or thymoma (N=40). SSTR2 expression was identified in 29 (of 80, 36.3%) TET including 2/2 (100%) small cell carcinomas, 2/5 (40.0%) atypical carcinoid tumors, 16/23 (69.6%) squamous cell carcinomas, 2/2 (100%) lymphoepithelial carcinomas, 1/1 (100%) adenosquamous carcinoma, and 6/40 (15.0%) thymomas. SSTR2 expression in ≥50% of tumor cells (vs 1-49%) was associated with younger age (p=0.023) and shorter recurrence/metastasis-free survival (p=0.007). 68Ga-DOTATATE PET scans (N=9) revealed a Krenning score of 3 in patients with atypical carcinoid tumor, small cell carcinoma, and squamous cell carcinoma (N=1 each) with SSTR2 expression in 95, 100, and 5% of tumor cells, respectively. Scans with Krenning scores of ≤2 (N=5) were seen in tumors with no SSTR2 expression in 80% of cases and a single atypical carcinoid tumor with SSTR2 expression in 10% of tumor cells. One scan resulted as "increased uptake" was in a patient with no SSTR2 expression. In conclusion, 68Ga-DOTATATE PET scans correlated with SSTR2 expression in TET in most patients and appeared to be useful to identify patients with TET who may be amenable to treatment with somatostatin analogues. Larger studies including more patients with 68Ga-DOTATATE PET scans are necessary to independently and prospectively validate our findings.

Extramedullary disease in multiple myeloma.

When clonal plasma cells grow at anatomic sites distant from the bone marrow or grows contiguous from osseous lesions that break through the cortical bone, it is referred to as extramedullary multiple myeloma (EMD). EMD remains challenging from a therapeutic and biological perspective. The pathogenetic mechanisms are not completely understood and it is generally associated with high-risk cytogenetics which portends poor outcomes. There is a rising incidence of EMD in the era of novel agents, likely a reflection of longer OS, with no standard treatment approach. Patients benefit from aggressive chemotherapy-based approaches, but the OS and prognosis remains poor. RT has been used for palliative care. There is a need for large prospective trials for development of treatment approaches for treatment of EMD.

Outcomes of COVID-19 in Patients With Cancer: A Closer Look at Pre-Emptive Routine Screening Strategies.

PURPOSE: The benefit of routine pre-emptive screening for severe acute respiratory syndrome coronavirus 2 infections in patients with cancer before cancer-directed therapies is unclear. Herein, we characterize the outcomes of a cohort of patients with cancer who were diagnosed with COVID-19 by routine screening (RS) in comparison with those diagnosed on the basis of clinical suspicion or exposure history (nonroutine screening [NRS]). METHODS: A multisite prospective observational study was conducted at three major and five satellite campuses of the Mayo Clinic Cancer Center between March 18 and July 31, 2020. The primary outcome was COVID-19-related hospital admission. Secondary outcomes included intensive care unit admissions and all-cause mortality. RESULTS: Five thousand four hundred fifty-two patients underwent RS in the outpatient setting only, and 44 (0.81%) were diagnosed with COVID-19. RS detected 19 additional patients from the scheduled inpatient admissions for surgical or interventional procedures or inpatient chemotherapy. One hundred sixty-one patients were diagnosed with COVID-19 on the basis of NRS. COVID-19-related hospitalization rate (17.5% v 26.7%; P = .14), intensive care unit admission (1.6% v 5.6%; P = .19), and mortality (4.8% v 3.7%; P = .72) were not significantly different between the RS and NRS groups. In the multivariable analysis, age ≥ 60 years (odds ratio, 4.4; P = .023) and an absolute lymphocyte count ≤ 1.4 × 109/L (odds ratio, 9.2; P = .002) were independent predictors of COVID-19-related hospital admission. CONCLUSION: The COVID-19 positivity rate was low on the basis of RS. Comparing the hospital admission and mortality outcomes with the NRS cohort, there were no significant differences. The value of routine pre-emptive screening of asymptomatic patients with cancer for COVID-19 remains low.

Immunotherapy in patients with autoimmune disease.

Immune checkpoint inhibitors (ICIs) such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1) and programmed cell death protein ligand 1 (PD-L1) inhibitors are widely used for the treatment of multiple cancers. Seven of these agents are currently FDA approved in the US as first or second line options for solid tumors and hematologic malignancies. These agents work by downregulating pathways that suppress T-cell activation and thereby mounting an immune response to the tumor. In general, ICI are well tolerated with only mild to moderate toxicity. However, in some patients severe immune-related adverse events (irAEs) that mimic the presentation of autoimmune diseases (AID) may occur. It is believed that irAEs occur due to disruption of immunologic self-tolerance, a mechanism that also seems to explain AID. Patients with pre-existing AID are usually excluded from prospective clinical trials due to concerns for flares of the underline AID. There is limited retrospective evidence supporting the use of ICI in patients with some pre-existing AID. These patients have an increased risk of malignancy and there is an unmet need to study ICIs in this population. This manuscript intends to review the current available evidence for the safety and activity of ICIs in patients with pre-existing AID. We summarize the reported use of ICI in patients with pre-existing AID according to the primary tumor site and type of ICI used.

Neutrophil to lymphocyte ratio as a prognostic marker in metastatic gallbladder cancer.

BACKGROUND: Neutrophil-to-lymphocyte ratio (NLR) has been used as an inflammation based prognostic marker for various malignancies. This study evaluated the association between NLR and overall survival (OS) in patients with metastatic gallbladder cancer (GBC) METHODS: An optimal cut off point for NLR was identified by plotting spline-based hazard ratio curves to identify a threshold effect and patients were divided into two groups, ≥5 or <5. Kaplan-Meier curves were plotted for NLR≥5 and NLR<5 and OS between the two groups. RESULTS: Of the 231 patients included, 138 (60%) had NLR <5 and 93 (40%) had NLR ≥5. There were no significant differences noted in gender, race, and administration of chemotherapy between the two groups. On univariable analysis, patients with NLR ≥5 had a significantly poor OS compared to those with NLR <5 (Median OS: 3.6 vs 8.7 months, p < 0.001). On multivariable analysis, adjusting for age, performance status, albumin, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, bilirubin, platelet count and no administration of chemotherapy, NLR of ≥5 was associated with a worse OS compared to NLR <5 (HR: 1.70, 95%CI:1.20-2.39, p < 0.05). CONCLUSION: The current study demonstrates that NLR ≥5 is an independent predictor of poor prognosis in patients with metastatic GBC.

Author Correction: Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas.

Purpose To evaluate ability of radiomic (computer-extracted imaging) features to distinguish non-small cell lung cancer adenocarcinomas from granulomas at noncontrast CT. Materials and Methods For this retrospective study, screening or standard diagnostic noncontrast CT images were collected for 290 patients (mean age, 68 years; range, 18-92 years; 125 men [mean age, 67 years; range, 18-90 years] and 165 women [mean age, 68 years; range, 33-92 years]) from two institutions between 2007 and 2013. Histopathologic analysis was available for one nodule per patient. Corresponding nodule of interest was identified on axial CT images by a radiologist with manual annotation. Nodule shape, wavelet (Gabor), and texture-based (Haralick and Laws energy) features were extracted from intra- and perinodular regions. Features were pruned to train machine learning classifiers with 145 patients. In a test set of 145 patients, classifier results were compared against a convolutional neural network (CNN) and diagnostic readings of two radiologists. Results Support vector machine classifier with intranodular radiomic features achieved an area under the receiver operating characteristic curve (AUC) of 0.75 on the test set. Combining radiomics of intranodular with perinodular regions improved the AUC to 0.80. On the same test set, CNN resulted in an AUC of 0.76. Radiologist readers achieved AUCs of 0.61 and 0.60, respectively. Conclusion Radiomic features from intranodular and perinodular regions of nodules can distinguish non-small cell lung cancer adenocarcinomas from benign granulomas at noncontrast CT. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Nishino in this issue.

Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas.

Adenocarcinomas and active granulomas can both have a spiculated appearance on computed tomography (CT) and both are often fluorodeoxyglucose (FDG) avid on positron emission tomography (PET) scan, making them difficult to distinguish. Consequently, patients with benign granulomas are often subjected to invasive surgical biopsies or resections. In this study, quantitative vessel tortuosity (QVT), a novel CT imaging biomarker to distinguish between benign granulomas and adenocarcinomas on routine non-contrast lung CT scans is introduced. Our study comprised of CT scans of 290 patients from two different institutions, one cohort for training (N = 145) and the other (N = 145) for independent validation. In conjunction with a machine learning classifier, the top informative and stable QVT features yielded an area under receiver operating characteristic curve (ROC AUC) of 0.85 in the independent validation set. On the same cohort, the corresponding AUCs for two human experts including a radiologist and a pulmonologist were found to be 0.61 and 0.60, respectively. QVT features also outperformed well known shape and textural radiomic features which had a maximum AUC of 0.73 (p-value = 0.002), as well as features learned using a convolutional neural network AUC = 0.76 (p-value = 0.028). Our results suggest that QVT features could potentially serve as a non-invasive imaging biomarker to distinguish granulomas from adenocarcinomas on non-contrast CT scans.

Post-treatment changes in hematological parameters predict response to nivolumab monotherapy in non-small cell lung cancer patients.

BACKGROUND: The absolute neutrophil count (ANC), absolute lymphocyte count (ALC), absolute monocyte count (AMC) and neutrophil to lymphocyte ratio (NLR) are known markers of inflammation. We evaluated whether ANC, ALC, AMC and NLR, both before and after treatment with nivolumab, are indicative markers of overall survival (OS) and evaluated change in NLR as a predictive marker of response in non -small cell lung cancer (NSCLC) patients treated with nivolumab. METHODS: A total of 109 patients with advanced NSCLC treated with nivolumab were included. ANC, ALC, AMC and NLR were examined at initiation of nivolumab therapy and after two cycles. The prognostic role of ANC, ALC, AMC and NLR with OS and changes in NLR ratio were examined with Kaplan-Meier curves and proportional hazard model. RESULT: Post-treatment NLR ≥5 after two cycles of nivolumab was associated with poor OS (median OS in NLR = <5 vs NLR = ≥5 was 29.1 (16.2-40.9) vs 24.2(16.1-36.2) months respectively, p<0.001). In addition NLR increased in non-responders after two cycles of nivolumab by 6.6±21.8 as compared to responders (p = 0.027). CONCLUSIONS: Post-treatment ANC, ALC and NLR are independent prognostic factors in NSCLC patients treated with nivolumab. Changes in NLR can be an early biomarker for response in NSCLC patients treated with nivolumab.

Premature Clinical Trial Discontinuation in the Era of Immune Checkpoint Inhibitors.

BACKGROUND: Clinical trial completion is critical for new cancer therapies. Premature trial termination or withdrawal is common and impairs progress. We assessed factors of early terminated/withdrawn oncology trials focusing on trials with immune checkpoint inhibitors (ICI), hypothesizing that the latter may be associated with lower rates of premature discontinuation. MATERIALS AND METHODS: We reviewed all adult, intervention, oncology trials registered in ClinicalTrials.gov (November 16, 2011, to April 16, 2015) to identify all terminated/withdrawn trials and reasons for termination. Logistics regression model was used to identify factors associated with early termination/withdrawal. Discontinuation rate was compared in trials with and without ICI. RESULTS: We identified 12,875 trials (35% industry funded, 12% federal funded), of which 8.5% were prematurely terminated (5%) or withdrawn (3.5%); the main reasons were poor accrual (33%) and logistical (24%). ICI trials (n = 350) had a nonsignificant lower rate of termination or withdrawal compared with all other oncology trials (5.4% vs. 8.5%; p = .9) and were less likely to discontinue due to poor accrual (nonsignificant difference: 21% vs. 33%; p = .4). ICI trials were also less likely to discontinue compared with all other oncology drug trials (e.g., chemotherapy, targeted inhibitors, antiangiogenesis, biologics; 5.4% vs. 7.9%, respectively, nonsignificant difference). The 4-year cumulative incidence of failing to complete for reasons unrelated to toxicity or efficacy was 18% (95% confidence interval 16%-20%). There was no association between annual incidence across different tumor types or accrual goal and rate of trial termination. CONCLUSION: Poor accrual represents the main cause of early cancer trial termination. Premature termination/withdrawal rate was not significantly lower in ICI compared with other trials. Clinical trial completion remains a high priority and can be influenced by provider and patient factors. IMPLICATIONS FOR PRACTICE: Clinical trial completion is critical for new cancer therapies. Premature trial termination or withdrawal is common and impairs progress. This study assessed factors of early terminated/withdrawn oncology trials, focusing on trials with immune checkpoint inhibitors (ICI), and found that poor accrual represents the main cause of early cancer trial termination. Premature termination/withdrawal rate was not significantly lower in immune checkpoint inhibitor trials compared to other trials. The discussion herein is focused on measures taken by the National Cancer Institute and other institutions to improve clinical trial accrual and prevent premature clinical trial discontinuation.

Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography.

Differentiation between benign and malignant nodules is a problem encountered by radiologists when visualizing computed tomography (CT) scans. Adenocarcinomas and granulomas have a characteristic spiculated appearance and may be fluorodeoxyglucose avid, making them difficult to distinguish for human readers. In this retrospective study, we aimed to evaluate whether a combination of radiomic texture and shape features from noncontrast CT scans can enable discrimination between granulomas and adenocarcinomas. Our study is composed of CT scans of 195 patients from two institutions, one cohort for training ([Formula: see text]) and the other ([Formula: see text]) for independent validation. A set of 645 three-dimensional texture and 24 shape features were extracted from CT scans in the training cohort. Feature selection was employed to identify the most informative features using this set. The top ranked features were also assessed in terms of their stability and reproducibility across the training and testing cohorts and between scans of different slice thickness. Three different classifiers were constructed using the top ranked features identified from the training set. These classifiers were then validated on the test set and the best classifier (support vector machine) yielded an area under the receiver operating characteristic curve of 77.8%.

Safety and Efficacy of PD-1/PD-L1 Inhibitors in Treatment-Naive and Chemotherapy-Refractory Patients With Non-Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis.

INTRODUCTION: Programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitors show significant clinical activity in non-small-cell lung carcinoma (NSCLC). However, there is a relative lack of data on comparative efficacy of these drugs in the first-line setting versus chemotherapy-treated patients. We compared the efficacy and toxicity of these drugs in these 2 distinct groups of patients. MATERIALS AND METHODS: Electronic databases (PubMed-Medline, EMBASE, Scopus) and major conference proceedings were systematically searched for all phase I to III clinical trials in NSCLC using PD-1/PD-L1 inhibitors. Objective response rate (ORR) and progression-free survival (PFS) data were collected and combined using DerSimonian and Laird random effects model meta-analysis. The I2 statistic was used to assess heterogeneity. RESULTS: Seventeen distinct trials (8 with treatment-naive patients [n = 937]; 14 with chemotherapy-treated patients [n = 3620]; 5 with separate treatment-naive and previously treated arms) were included. Treatment-naive patients had a statistically significant higher ORR (30.2%; 95% confidence interval [CI], 22.70-38.2) than patients previously treated with chemotherapy (ORR, 20.1%; 95% CI, 17.5-22.9; P = .02). No significant differences in PFS were observed between the 2 groups. Treatment-naive patients had statistically significant higher rates of all grade pneumonitis compared with previously treated patients (4.9%; 95% CI, 3.4-6.7 vs. 3.0%; 95% CI, 2.0-4.1; P = .04); however, no significant differences in any other immune-related adverse events were observed. CONCLUSION: PD-1/PD-L1 inhibitor therapy for advanced NSCLC has a significantly higher ORR and a higher rate of immune-mediated pneumonitis when used in the first-line setting compared with chemotherapy treated patients.

Incidence of Pneumonitis With Use of Programmed Death 1 and Programmed Death-Ligand 1 Inhibitors in Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis of Trials.

BACKGROUND: Programmed death 1 (PD-1) programmed death-ligand 1 (PD-L1) inhibitors show significant clinical activity in non-small cell lung carcinoma (NSCLC). However, they are often associated with potentially fatal immune-mediated pneumonitis. Preliminary reports of trials suggest a difference in the rate of pneumonitis with PD-1 and PD-L1 inhibitors. We sought to determine the overall incidence of pneumonitis and differences according to type of inhibitors and prior chemotherapy use. METHODS: MEDLINE, Embase, and Scopus databases were searched up to November 2016. Rates of pneumonitis of any grade and grade ≥ 3 from all clinical trials investigating nivolumab, pembrolizumab, atezolizumab, durvalumab, and avelumab as single agents in NSCLC were collected. The incidence of pneumonitis across trials was calculated using DerSimonian-Laird random effects models. We compared incidences between PD-1 and PD-L1 inhibitors and between treatment naive and previously treated patients. RESULTS: Nineteen trials (12 with PD-1 inhibitors [n = 3,232] and 7 with PD-L1 inhibitors [n = 1,806]) were identified. PD-1 inhibitors were found to have statistically significant higher incidence of any grade pneumonitis compared with PD-L1 inhibitors (3.6%; 95% CI, 2.4%-4.9% vs 1.3%; 95% CI, 0.8%-1.9%, respectively; P = .001). PD-1 inhibitors were also associated with higher incidence of grade 3 or 4 pneumonitis (1.1%; 95% CI, 0.6%-1.7% vs 0.4%; 95% CI, 0%-0.8%; P = .02). Treatment naive patients had higher incidence of grade 1 through 4 pneumonitis compared with previously treated patients (4.3%; 95% CI, 2.4%-6.3% vs 2.8%; 95% CI, 1.7%- 4%; P = .03). CONCLUSIONS: There was a higher incidence of pneumonitis with use of PD-1 inhibitors compared with PD-L1 inhibitors. Higher rate of pneumonitis was more common in treatment naive patients.

An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT.

PURPOSE: Distinguishing between benign granulmoas and adenocarcinomas is confounded by their similar visual appearance on routine CT scans. Unfortunately, owing to the inability to discriminate these lesions radigraphically, many patients with benign granulomas are subjected to unnecessary surgical wedge resections and biopsies for pathologic confirmation of cancer presence or absence. This suggests the need for improved computerized characterization of these nodules in order to distinguish between these two classes of lesions on CT scans. While there has been substantial interest in the use of textural analysis for radiomic characterization of lung nodules, relatively less work has been done in shape based characterization of lung nodules, particularly with respect to granulmoas and adenocarcinomas. The primary goal of this study is to evaluate the role of 3D shape features for discrimination of benign granulomas from malignant adenocarcinomas on lung CT images. Towards this end we present an integrated framework for segmentation, feature characterization and classification of these nodules on CT. METHODS: The nodule segmentation method starts with separation of lung regions from the surrounding lung anatomy. Next, the lung CT scans are projected into and represented in a three dimensional spectral embedding (SE) space, allowing for better determination of the boundaries of the nodule. This then enables the application of a gradient vector flow active contour (SEGvAC) model for nodule boundary extraction. A set of 24 shape features from both 2D slices and 3D surface of the segmented nodules are extracted, including features pertaining to the angularity, spiculation, elongation and nodule compactness. A feature selection scheme, PCA-VIP, is employed to identify the most discriminating set of features to distinguish granulmoas from adenocarcinomas within a learning set of 82 patients. The features thus identified were then combined with a support vector machine classifier and independently validated on a distinct test set comprising 67 patients. The performance of the classifier for both of the training and validation cohorts was evaluated by the area under receiver characteristic curve (ROC). RESULTS: We used 82 and 67 studies from two different institutions respectively for training and independent validation of the model and the shape features. The Dice coefficient between automatically segmented nodules by SEGvAC and the manual delineations by expert radiologists (readers) was 0.84± 0.04 whereas inter-reader segmentation agreement was 0.79± 0.12. We also identified a set of consistent features (Roughness, Convexity and Spherecity) that were found to be strongly correlated across both manual and automated nodule segmentations (R > 0.80, p < 0.0001) and capture the marginal smoothness and 3D compactness of the nodules. On the independent validation set of 67 studies our classifier yielded a ROC AUC of 0.72 and 0.64 for manually- and automatically segmented nodules respectively. On a subset of 20 studies, the AUCs for the two expert radiologists and 1 pulmonologist were found to be 0.82, 0.68 and 0.58 respectively. CONCLUSIONS: The major finding of this study was that certain shape features appear to differentially express between granulomas and adenocarcinomas and thus computer extracted shape cues could be used to distinguish these radiographically similar pathologies.

Programmed Cell Death 1 (PD-1) Ligand (PD-L1) Expression in Solid Tumors As a Predictive Biomarker of Benefit From PD-1/PD-L1 Axis Inhibitors: A Systematic Review and Meta-Analysis.

PURPOSE: Drugs targeting the programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) pathway show significant clinical activity across several tumor types. However, a majority of patients do not respond to these agents. Use of biomarker assays to predict response to these agents is an active area of research; however, the predictive value of PD-L1 immunohistochemistry (IHC) assays is largely inconsistent across clinical trials. In this meta-analysis of clinical trials of PD-1/PD-L1-targeted agents, we evaluate the predictive value of a tumor and tumor-infiltrating immune cell PD-L1 IHC assay as a biomarker for objective response to PD-1/PD-L1 inhibitors. METHODS: We searched databases (PubMed, Medline, ASCO abstracts, European Society for Medical Oncology abstracts, and Scopus) up until December 2016 for clinical trials using PD-1/PD-L1 inhibitors with reported PD-L1 biomarker data. Objective response rates (primary end point) from all phase I to III trials investigating nivolumab, pembrolizumab, atezolizumab, durvalumab, and avelumab in advanced solid tumors were collected. Odds ratios (ORs) for response in PD-L1-positive patients compared with PD-L1-negative patients were calculated using the DerSimonian-Laird random effects model to combine trials. We performed meta-analysis as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS: Forty-one distinct trials with 6,664 patients were identified. PD-L1 expression was predictive of favorable response across all tumor types (OR, 2.26; 95% CI, 1.85 to 2.75; P < .001), with the significantly largest effect observed in non-small-cell lung cancer (OR, 2.51; 95% CI, 1.99 to 3.17; P < .001). A subgroup analysis across all non-small-cell lung cancer trials using nivolumab and Dako clone 28-8 (Dako, Carpinteria, CA) IHC antibody assay yielded a significantly higher objective response rate in patients with tumor PD-L1 expression even at the minimum cutoff value of 1% (OR, 2.17; 95% CI, 1.03 to 4.57). CONCLUSION: Our meta-analysis shows that tumor and tumor-infiltrating immune cell PD-L1 overexpression based on IHC is associated with significantly higher response rates to PD-1/PD-L1 axis inhibitors across a range of malignant solid tumors.

Ipilimumab-induced colitis in patients with metastatic melanoma.

Ipilimumab is used for the treatment of metastatic melanoma and is associated with serious immune-related colitis. We aimed to report the clinical features, treatment, and outcomes of patients with ipilimumab-induced colitis. In this retrospective observational study, we identified patients with unresectable melanoma treated with ipilimumab between March 2011 and September 2013. Diarrhea was assessed using the Common Terminology Criteria for Adverse Events, v3.0. Colitis was defined by diarrhea (grade≥2) requiring steroids with or without endoscopic/histologic/radiologic evidence of colitis. A total of 103 patients with metastatic melanoma treated with ipilimumab were identified. Of these, 30 patients (29%) developed diarrhea (all grades), and 23 patients (22%) developed colitis requiring systemic corticosteroid therapy. The median number of ipilimumab doses before onset of diarrhea was 2 (range, 1-4). Six of 23 patients responded to less than 1 mg/kg daily prednisone alone. Fifteen patients required high-dose oral and/or intravenous prednisone (1-2 mg/kg body weight). Six patients had diarrhea refractory to prednisone; five required rescue therapy with budesonide (9-12 mg daily) and one was treated with infliximab (5 mg/kg, three doses). There was one case of severe diarrhea (grade 3) treated successfully with high-dose budesonide (12 mg) monotherapy. Ipilimumab-induced colitis requires early and aggressive medical therapy. Most patients can be successfully managed with systemic corticosteroids. High-dose budesonide is an attractive steroid-sparing agent, however further studies of its efficacy in this setting are needed. Infliximab should be used in refractory cases to avoid colectomy.