Artificial intelligence (AI) is a disruptive technology that involves the use of computerised algorithms to dissect complicated data. Among the most promising clinical applications of AI is diagnostic imaging, and mounting attention is being directed at establishing and fine-tuning its performance to facilitate detection and quantification of a wide array of clinical conditions. Investigations leveraging computer-aided diagnostics have shown excellent accuracy, sensitivity, and specificity for the detection of small radiographic abnormalities, with the potential to improve public health. However, outcome assessment in AI imaging studies is commonly defined by lesion detection while ignoring the type and biological aggressiveness of a lesion, which might create a skewed representation of AI's performance. Moreover, the use of non-patient-focused radiographic and pathological endpoints might enhance the estimated sensitivity at the expense of increasing false positives and possible overdiagnosis as a result of identifying minor changes that might reflect subclinical or indolent disease. We argue for refinement of AI imaging studies via consistent selection of clinically meaningful endpoints such as survival, symptoms, and need for treatment.
Purpose of Review Multiple myeloma is the second most common hematologic malignancy in the USA, with over 32,000 new cases and nearly 13,000 deaths expected in 2019. The past few decades in myeloma research have yielded significant advances, leading to the expansion of novel anti-myeloma agents. This review describes the incidence and mechanisms of cardiotoxicity for the FDA-approved proteasome inhibitors in myeloma and proposes strategies to assess and manage resultant cardiovascular adverse events. Recent Findings Proteasome inhibition precipitates protein aggregation and alters transcriptional activation of NF-κB targets which contributes to a pro-apoptotic signaling cascade in myeloma cells. Similar effects in cardiomyocytes and vascular smooth muscle endothelium, along with off-target downregulation of autophagy and signaling alterations of nitric oxide homeostasis, may be linked to observed cardiotoxic effects. There is preliminary evidence for cardioprotective potential for rutin, dexrazoxane, and apremilast that could have clinical applicability in the future. Summary Of the proteasome inhibitors used in clinical practice, carfilzomib is the most strongly associated with cardiotoxicity. Patients with anticipated carfilzomib treatment should undergo assessment and optimization of baseline cardiovascular risk, with close monitoring during treatment. Previous clinical trials were not specifically designed to assess proteasome inhibitor-related cardiotoxicity, creating a need for future studies to identify and risk stratify vulnerable individuals and to develop potential cardioprotective strategies in attenuating cardiac injury.
Whether cardiovascular (CV) disease is associated with clinical outcomes in cancer patients receiving immunotherapy is unknown. We reviewed the Mayo Clinic database for all cancer patients who received an immune checkpoint inhibitor (ICI). Multivariate logistic regression analysis, survival analyses, and Cox proportional-hazards models were formulated. Between March, 2010 and July, 2019, 3,326 patients received ICI. Mean patient age was 63.5 years (range: 16 to 96 years). In a Cox proportional-hazards model, obesity (hazard ratio [HR] 0.65, 95% confidence level [CI] 0.55 to 0.77, p < 0.001) and hypercholesterolemia (HR 0.80, 95% CI 0.72 to 0.89, p < 0.001) were associated with lower all-cause mortality while hypertension (HR 1.32, 95% CI 1.17 to 1.49, p < 0.001) and smoking (HR 1.17, 95% CI 1.06 to 1.29, p = 0.002) were associated with higher overall mortality. Among patients with lung cancer, multivariable-adjusted hazard ratios for death from any cause for beta blocker users, as compared with patients who had never used a beta blocker, were 1.39 (95% CI 1.10 to 1.76, p = 0.006). A total of 80 patients (2.4%) experienced CV immune-related adverse events. Event-related morality for ICI-induced myocarditis was 41.7% (5/12). Multivariableadjusted hazard ratios for ICI-induced myocarditis were 5.2 (95% CI 1.4 to 18.7, p = 0.01) for history of heart failure, 4.06 (95% CI 1.15 to 14.3, p = 0.03) for history of acute coronary syndrome, and 1.07 (per each 1-year increase, 95% CI 1.01 to 1.14, p = 0.02) for age. In conclusion, our study shows that CV factors are associated with clinical outcomes in cancer patients receiving ICI and could be used to predict mortality. In patients with lung cancer, pretreatment beta blocker use is associated with higher all-cause mortality. Three clinical factors-history of heart failure, history of acute coronary syndrome, and age greater than 80 years-help identify patients at higher risk of ICI-induced myocarditis who might benefit from more intensive cardiac surveillance.
Despite modest effects from initiatives such as the Choosing Wisely campaign, unnecessary diagnostic imaging remains a substantial problem in the United States. [1][2][3] Significant between-country differences probably reflect largely wasted overuse. The United States occupies top usage ranks, with population rates of annual computed tomography (CT) scans (245 per 1000 people) and magnetic resonance imaging (MRI) scans (118 per 1000 people) 2 that are 5 and 3 times higher than those of Finland, respectively. With aggressive testing, the yield of useful information increases only slightly. Further, some diagnostic tests generate the detection of mostly incidental findings ("incidentalomas") with the frequency proportional to the excess of testing performed.Radiographic incidentalomas, defined as abnormalities that did not serve as the native reason for the performance of the test, are very common. 4 These findings have major financial and health consequences, including further wasted efforts for unnecessary diagnosis and treatment and patient anxiety. 5 Much of the focus to date has been on the management of incidentalomas rather than their adverse consequences. These
Dramatic advances have been made in the understanding of cancer over the past decade. Prime among those are better appreciation of the biology of cancer and the development of targeted therapies. Despite these improvements, however, most tumors remain refractory to anti-cancer medications and frequently recur. Cancer Stem Cells (CSCs), which in some cases express markers of pluripotency (e.g., Oct-4), share many of the molecular features of normal stem cells. These cells have been hypothesised to play a role in tumor resistance and relapse. They exhibit dependence on many primitive regulatory pathways and may be best viewed in the context of embryonic signaling pathways. In this article, we review important embryonic signaling cascades and their differential expression in CSCs. We also discuss these pathways as actionable targets for novel therapies in hopes that eliminating cancer stem cells will lead to an improvement in overall survival for patients.
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