RESUMEN
Lung cancer is the second most common malignancy in both genders and the most common cause of cancer-related deaths worldwide. Broadly, lung cancer is divided into two types: small-cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). Non-small cell lung cancer accounts for 85% of the diagnoses of lung cancer. It is necessary to check for any targetable mutations, which can help in deciding the treatment plan for the patients. The patient we are reporting is a 70-year-old male with multiple co-morbidities diagnosed with non-small cell carcinoma, favoring adenocarcinoma on histopathology. He was started on Atezolizumab/Bevacizumab/Carboplatin/Paclitaxel (ABCP). He was switched to maintenance Atezolizumab/Bevacizumab after four cycles due to poor tolerance to carboplatin and paclitaxel. The patient presented with neutropenic colitis and acute kidney injury (AKI), requiring admission. workup revealed nephrotic range proteinuria with a high urinary albumin-to-creatinine ratio. He underwent a renal biopsy to ascertain the cause of his proteinuria, which showed marked acute and chronic tubulo-interstitial nephritis (TIN), amyloidosis, and global glomerulosclerosis. Secondary (AA) amyloidosis is characterized by the extracellular deposition of misfolded proteins. Although interstitial nephritis is a reported side effect of immune checkpoint inhibitors, AA amyloidosis is a rarer side effect. So, to determine the exact cause and early therapeutic intervention in immune checkpoint inhibitor-related kidney injury, large retrospective or prospective studies should be done.
RESUMEN
Defective repair of DNA when heterozygous leads to Lynch syndrome (LS) which is inherited in an autosomal dominant fashion. When homozygous, defective repair of DNA leads to constitutional mismatch repair deficiency syndrome (CMMRD), inherited in an autosomal recessive fashion with a predisposition to develop a pattern of childhood malignancies including hematological and solid cancers. We report such a case of a 21-year-old male who developed anaplastic astrocytoma, Burkitt lymphoma, osteochondroma, and colon cancer successively. Each cancer was treated successfully except for colon cancer which developed liver metastasis after the initial treatment with curative intent. However, the patient has been treated for liver metastasis with curative intent and is currently on follow-up. This case report highlights the importance of maintaining a low threshold for investigating CMMRD and other potential cancer predisposition syndromes when a patient presents with multiple cancers in the early years of their life.
RESUMEN
As the world grapples with the problem of the coronavirus disease 2019 (COVID-19) pandemic and its devastating effects, scientific groups are working towards solutions to mitigate the effects of the virus. This paper aimed to collate information on COVID-19 prediction models. A systematic literature review is reported, based on a manual search of 1,196 papers published from January to December 2020. Various databases such as Google Scholar, Web of Science, and Scopus were searched. The search strategy was formulated and refined in terms of subject keywords, geographical purview, and time period according to a predefined protocol. Visualizations were created to present the data trends according to different parameters. The results of this systematic literature review show that the study findings are critically relevant for both healthcare managers and prediction model developers. Healthcare managers can choose the best prediction model output for their organization or process management. Meanwhile, prediction model developers and managers can identify the lacunae in their models and improve their data-driven approaches.
RESUMEN
As the world grapples with the problem of the coronavirus disease 2019 (COVID-19) pandemic and its devastating effects, scientific groups are working towards solutions to mitigate the effects of the virus. This paper aimed to collate information on COVID-19 prediction models. A systematic literature review is reported, based on a manual search of 1,196 papers published from January to December 2020. Various databases such as Google Scholar, Web of Science, and Scopus were searched. The search strategy was formulated and refined in terms of subject keywords, geographical purview, and time period according to a predefined protocol. Visualizations were created to present the data trends according to different parameters. The results of this systematic literature review show that the study findings are critically relevant for both healthcare managers and prediction model developers. Healthcare managers can choose the best prediction model output for their organization or process management. Meanwhile, prediction model developers and managers can identify the lacunae in their models and improve their data-driven approaches.