More than two years after the onset of the COVID-19 pandemic, healthcare providers are facing an emergency within an emergency, the so-called long COVID or post-COVID-19 syndrome (PCS). Patients diagnosed with PCS develop an extended range of persistent symptoms and/or complications from COVID-19. The risk factors and clinical manifestations are many and various. Advanced age, sex/gender, and pre-existing conditions certainly influence the pathogenesis and course of this syndrome. However, the absence of precise diagnostic and prognostic biomarkers may further complicate the clinical management of patients. This review aimed to summarize recent evidence on the factors influencing PCS, possible biomarkers, and therapeutic approaches. Older patients recovered approximately one month earlier than younger patients, with higher rates of symptoms. Fatigue during the acute phase of COVID-19 appears to be an important risk factor for symptom persistence. Female sex, older age, and active smoking are associated with a higher risk of developing PCS. The incidence of cognitive decline and the risk of death are higher in PCS patients than in controls. Complementary and alternative medicine appears to be associated with improvement in symptoms, particularly fatigue. The heterogeneous nature of post-COVID symptoms and the complexity of patients with PCS, who are often polytreated due to concomitant clinical conditions, suggest a holistic and integrated approach to provide useful guidance for the treatment and overall management of long COVID.

Pharmacogenomics can identify polymorphisms in genes involved in drug pharmacokinetics and pharmacodynamics determining differences in efficacy and safety and causing inter-individual variability in drug response. Therefore, pharmacogenomics can help clinicians in optimizing therapy based on patient’s genotype, also in psychiatric and neurological settings. However, pharmacogenetic screenings for psychotropic drugs are not routinely employed in diagnosis and monitoring of patients treated with mood stabilizers, such as carbamazepine and valproate, because their benefit in clinical practice is still controversial. In this review, we summarize the current knowledge on pharmacogenetic biomarkers of these anticonvulsant drugs.

Natural Health Products (NHPs) have long been considered a valuable therapeutic approach for the prevention and treatment of various diseases, including cancer. However, research on this topic has led to inconclusive and often controversial results. This review aims to provide a comprehensive update of the effects and mechanisms related to the use of NHPs, to describe the results of randomized clinical trials (RCTs) on their effects in cancer patients, and to critically discuss factors influencing clinical outcomes. RCTs available in the literature, even those studying the same NHP, are very heterogeneous in terms of indications, doses, route and timing of administration, and outcomes evaluated. Silymarin, ginsenoside, and vitamin E appear to be useful in attenuating adverse events related to radiotherapy or chemotherapy, and curcumin and lycopene might provide some benefit in patients with prostate cancer. Most RCTs have not clarified whether NHP supplementation provides any real benefit, while harmful effects have been shown in some cases. Overall, the available data suggest that although there is some evidence to support the benefits of NHPs in the management of cancer patients, further clinical trials with the same design are needed before their introduction into clinical practice can be considered.

Rheumatoid arthritis (RA) is a chronic inflammatory disease that is very complex and heterogeneous. If not adequately treated, RA patients are likely to manifest excess of morbidity and disability with an important impact on the quality of life. Pharmacological treatment is based on the administration of the disease-modifying antirheumatic drugs (DMARDs), subdivided into conventional synthetic (csDMARDs), targeted synthetic (tsDMARDs), and biological (bDMARDs). bDMARDs are now frequently administered in patients, both as alternative treatment and together with csDMARDs. Unfortunately, there is a therapeutic response variability both to old and new drugs. Therefore, to identify pre-therapeutic and on-treatment predictors of response is a priority. This review aims to summarize recent advances in understanding the causes of the variability in treatment response in RA, with particular attention to predictive potential of autoantibodies and DMARD pharmacogenetics. In recent years, several biomarkers have been proposed to personalize the therapy. Unfortunately, a magic bullet does not exist, as many factors concur to disease susceptibility and treatment outcomes, acting around the patient’s congenital background. Models integrating demographic, clinical, biochemical, and genetic data are needed to enhance the predictive capacity of specific factors singularly considered to optimize RA treatment in light of multidisciplinary patient management.

Fluoropyrimidines (FP) are mainly metabolised by dihydropyrimidine dehydrogenase (DPD), encoded by the DPYD gene. FP pharmacogenetics, including four DPYD polymorphisms (DPYD-PGx), is recommended to tailor the FP-based chemotherapy. These polymorphisms increase the risk of severe toxicity; thus, the DPYD-PGx should be performed prior to starting FP. Other factors influence FP safety, therefore phenotyping methods, such as the measurement of 5-fluorouracil (5-FU) clearance and DPD activity, could complement the DPYD-PGx. We describe a case series of patients in whom we performed DPYD-PGx (by real-time PCR), 5-FU clearance and a dihydrouracil/uracil ratio (as the phenotyping analysis) and a continuous clinical monitoring. Patients who had already experienced severe toxicity were then identified as carriers of DPYD variants. The plasmatic dihydrouracil/uracil ratio (by high-performance liquid chromatography (HPLC)) ranged between 1.77 and 7.38. 5-FU clearance (by ultra-HPLC with tandem mass spectrometry) was measured in 3/11 patients. In one of them, it reduced after the 5-FU dosage was halved; in the other case, it remained high despite a drastic dosage reduction. Moreover, we performed a systematic review on genotyping/phenotyping combinations used as predictive factors of FP safety. Measuring the plasmatic 5-FU clearance and/or dihydrouracil/uracil (UH2/U) ratio could improve the predictive potential of DPYD-PGx. The upfront DPYD-PGx combined with clinical monitoring and feasible phenotyping method is essential to optimising FP-based chemotherapy.

Understanding the link between COVID-19 and patient immune characteristics is crucial. We previously demonstrated that high levels of the soluble Programmed Death-Ligand1 (sPD-L1) at the beginning of the infection correlated with low lymphocyte number and high C-reactive protein (CRP), longer length of stay (LOS), and death. This study investigated whether sPD-L1 can be a prognosis biomarker during COVID-19. Severe and non-severe COVID-19 patients were enrolled at the University Hospital of Salerno. During hospitalization, at admission, and after 12–14 days, patients’ data were collected, and sPD-L1 levels were measured by enzyme-linked immunosorbent assay. The peripheral lymphocyte number negatively correlated with the time of negativization (p = 0.006), length of stay (LOS) (p = 0.032), and CRP (p = 0.004), while sPD-L1 positively correlated with LOS (p = 0.015). Patients with increased sPD-L1 and lymphocyte number showed a shorter LOS than those with decreased sPD-L1 and lymphocyte number (p = 0.038) and those with increased sPD-L1 and decreased lymphocyte number (p = 0.025). Moreover, patients with increased sPD-L1 and decreased CRP had a shorter LOS than those with increased sPD-L1 and CRP (p = 0.034) and those with decreased sPD-L1 and CRP (p = 0.048). In conclusion, while at an early phase of COVID-19, sPD-L1 promotes an immune escape, later, it might act to dampen an excessive immune response, proving its role in COVID-19 prognosis.