Precision medicine and its implementation in patients with NTRK fusion genes: perspective from developing countries.

Precision oncology is the field that places emphasis on the diagnosis and treatment of tumors that harbor specific genomic alterations susceptible to inhibition or modulation. Although most alterations are only present in a minority of patients, a substantial effect on survival can be observed in this subgroup. Mass genome sequencing has led to the identification of a specific driver in the translocations of the tropomyosin receptor kinase family (NTRK) in a subset of rare tumors both in children and in adults, and to the development and investigation of Larotrectinib. This medication was granted approval by the US Food and Drug Administration for NTRK-positive tumors, regardless of histology or age group, as such, larotrectinib was the first in its kind to be approved under the premise that molecular pattern is more important than histology in terms of therapeutic approach. It yielded significant results in disease control with good tolerability across a wide range of diseases including rare pediatric tumors, salivary gland tumors, gliomas, soft-tissue sarcomas, and thyroid carcinomas. In addition, and by taking different approaches in clinical trial design and conducting allocation based on biomarkers, the effects of target therapies can be isolated and quantified. Moreover, and considering developing nations and resource-limited settings, precision oncology could offer a tool to reduce cancer-related disability and hospital costs. In addition, developing nations also present patients with rare tumors that lack a chance of treatment, outside of clinical trials. This, in turn, offers the possibility for international collaboration, and contributes to employment, education, and health service provisions. The reviews of this paper are available via the supplemental material section.

Mortality and Advanced Support Requirement for Patients With Cancer With COVID-19: A Mathematical Dynamic Model for Latin America.

PURPOSE: In the midst of a global pandemic, evidence suggests that similar to other severe respiratory viral infections, patients with cancer are at higher risk of becoming infected by COVID-19 and have a poorer prognosis. METHODS: We have modeled the mortality and the intensive care unit (ICU) requirement for the care of patients with cancer infected with COVID-19 in Latin America. A dynamic multistate Markov model was constructed. Transition probabilities were estimated on the basis of published reports for cumulative probability of complications. Basic reproductive number (R0) values were modeled with R using the EpiEstim package. Estimations of days of ICU requirement and absolute mortality were calculated by imputing number of cumulative cases in the Markov model. RESULTS: Estimated median time of ICU requirement was 12.7 days, median time to mortality was 16.3 days after infection, and median time to severe event was 8.1 days. Peak ICU occupancy for patients with cancer was calculated at 16 days after infection. Deterministic sensitivity analysis revealed an interval for mortality between 18.5% and 30.4%. With the actual incidence tendency, Latin America would be expected to lose approximately 111,725 patients with cancer to SARS-CoV-2 (range, 87,116-143,154 patients) by the 60th day since the start of the outbreak. Losses calculated vary between < 1% to 17.6% of all patients with cancer in the region. CONCLUSION: Cancer-related cases and deaths attributable to SARS-CoV-2 will put a great strain on health care systems in Latin America. Early implementation of interventions on the basis of data given by disease modeling could mitigate both infections and deaths among patients with cancer.