Antibiotic-Resistant Septicemia in Pediatric Oncology Patients Associated with Post-Therapeutic Neutropenic Fever

• Main Authors: Rosalino Vázquez-López, Omar Rivero Rojas, Andrea Ibarra Moreno, José Erik Urrutia Favila, Adan Peña Barreto, Guadalupe Lizeth Ortega Ortuño, Jorge Andrés Abello Vaamonde, Ivanka Alejandra Aguilar Velazco, José Marcos Félix Castro, Sandra Georgina Solano-Gálvez, Tomás Barrientos Fortes, Juan Antonio González-Barrios
• Format: Article
• Language: English
• Published: MDPI AG 2019-07-01
• Series: Antibiotics
• Subjects: childhood cancer; septicemia; multidrug-resistant (MDR) bacteria; extensively drug-resistant (XDR) bacteria; pandrug-resistant (PDR) bacteria; post-therapeutic neutropenic fever; Mexico
• Online Access: https://www.mdpi.com/2079-6382/8/3/106

Death in cancer patients can be caused by the progression of tumors, their malignity, or other associated conditions such as sepsis, which is a multiphasic host response to a pathogen that can be significantly amplified by endogenous factors. Its incidence is continuously rising, which reflects the increasing number of sick patients at a higher risk of infection, especially those that are elderly, pediatric, or immunosuppressed. Sepsis appears to be directly associated with oncological treatment and fatal septic shock. Patients with a cancer diagnosis face a much higher risk of infections after being immunosuppressed by chemotherapy, radiotherapy, or anti-inflammatory therapy, especially caused by non-pathogenic, Gram-negative, and multidrug-resistant pathogens. There is a notorious difference between the incidence and mortality rates related to sepsis in pediatric oncologic patients between developed and developing countries: they are much higher in developing countries, where investment for diagnosis and treatment resources, infrastructure, medical specialists, cancer-related control programs, and post-therapeutic care is insufficient. This situation not only limits but also reduces the life expectancy of treated pediatric oncologic patients, and demands higher costs from the healthcare systems. Therefore, efforts must aim to limit the progression of sepsis conditions, applying the most recommended therapeutic regimens as soon as the initial risk factors are clinically evident—or even before they are, as when taking advantage of machine learning prediction systems to analyze data.