Medical oncology
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With the emergence of second wave of COVID-19 infection globally, particularly in India in March-April 2021, protection by massive vaccination drive has become the need of the hour. Vaccines have been proved to reduce the risk of developing severe illness and are emerging as vital tools in the battle against COVID-19. ⋯ Nevertheless, a considerable degree of doubt, hesitancy and misconceptions are noted regarding the administration of vaccines particularly during active immuno-suppressant treatment. This review article highlights the added vulnerability of cancer patients to the COVID-19 infection and has explored the immunological challenges associated with malignancy, anticancer treatment and COVID-19 vaccination.
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Cancer patients are at particular risk from COVID-19 since they usually present multiple risk factors for this infection such as older age, immunosuppressed state, comorbidities (e.g., chronic lung disease, diabetes, cardiovascular diseases), need of frequent hospital admissions and visits. Therefore, in the COVID era, oncologists should carefully weigh risks/benefits when planning cancer therapies and follow-up appointments. Recently, several scientific associations developed specific guidelines or recommendations to help physicians in their clinical practice. This review focuses on main available guidelines/recommendations regarding the cancer patient management during the COVID-19 pandemic.
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Currently world is fighting with global pandemic of coronavirus disease 2019 (COVID-19). At this time of uncertainty, oncologists are struggling to provide appropriate care to cancer patients. ⋯ As cancer patients are immunocompromised and there are high chances of exposure during hospital visits and if they get infected, outcome can be fatal. So through the column of this article, we would like to provide basic guideline in management of cancer patients during COVID-19 pandemic.
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Artificial intelligence (AI) is revolutionizing healthcare and transforming the clinical practice of physicians across the world. Radiology has a strong affinity for machine learning and is at the forefront of the paradigm shift, as machines compete with humans for cognitive abilities. AI is a computer science simulation of the human mind that utilizes algorithms based on collective human knowledge and the best available evidence to process various forms of inputs and deliver desired outcomes, such as clinical diagnoses and optimal treatment options. ⋯ Concerns have been expressed reflecting opinions that future medicine based on AI will render radiologists irrelevant. Thus, how much of this is based on reality? To answer these questions, it is important to examine the facts, clarify where AI really stands and why many of these speculations are untrue. We aim to debunk the 6 top myths regarding AI in the future of radiologists.
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Meta Analysis
Effect of transplant status in CD19-targeted CAR T-cell therapy: a systematic review and meta-analysis.
Chimeric antigen receptor (CAR) T-cell therapy has shown promise for relapsed/refractory malignancies. Many patients have undergone prior hematopoietic stem cell transplant (HSCT), yet effects of transplant status on CAR T-cell therapy efficacy and safety have not been reported. The purpose of the study is to systematically evaluate the likelihood of achieving optimum response, severe cytokine release syndrome (sCRS), and neurotoxicity in the context of CAR T-cell therapy for HSCT-naïve patients versus those with prior HSCT. ⋯ Overall risk of bias was moderate. While pooled estimates showed an advantage among HSCT-naïve patients for achieving optimum response and increased likelihood for sCRS and neurotoxicity, findings were not statistically significant. Any differences in efficacy and safety of CAR T-cell therapy cannot be verifiably attributed to transplant status, and additional controlled trials with increased sample sizes are needed to determine whether suggestive patterns favoring HSCT-naïve patients are validated.