Blood biomarkers in the application of diagnosis and prediction of overall survival for 1089 patients with nasopharyngeal carcinoma

Abstract Previous studies have indicated that some blood metrics play a crucial role in the diagnostic and prognostic values of various solid tumours. However, their comprehensive and unbiased comparison for nasopharyngeal carcinoma (NPC) has not been performed. Twenty blood metrics evaluated in tumours or noncancerous diseases were selected. We selected 1089 patients with NPC and analyzed the relationship between these metrics, clinical characteristics, and overall survival (OS). The albumin and prognostic nutritional index (PNI) exhibited a high area under the curve (AUC) value (> 0.7) together with high “sensitivity (Sen) + specificity (Spe) (> 1.5)” or Youden index (> 0.5) when compared to healthy populations. In comparing NPC and nasal polyps, 9 of 20 blood metrics showed a high AUC value (> 0.7). However, only the PNI and international normalised ratio show a sufficiently high Sen + Spe or Youden Index. None of them could distinguish the status of the TNM classification well. Only the lymphocyte-to-monocyte ratio (LMR) could predict the OS of patients with NPC (cut-off, 4.91; p = 0.0069). Blood metrics as non-invasive biomarkers are valuable tools for clinical management. Among these indicators, PNI is the most ideal indicator to distinguish NPC from healthy and nasal polyps. The LMR has good prognostic value

Clinical experience using peripheral blood parameters to analyse the mutation type of thalassemia carriers in pregnant women

Thalassaemia is a typically monogenic disease caused by mutations or deletions in the globin gene and has a high prevalence in southern China. Prenatal screening for thalassaemia can be effective in reducing the incidence of thalassaemia. Haematologic parameters of pregnant thalassaemia carriers are diverse and potentially valuable for identifying different types of genotypes. By comparing and evaluating haematological parameters, formulas in the literature, we tried to reveal differences between pregnant women carrying different types of thalassaemia genes. The Mentzer formula (MCV/RBC) showed a strong ability to differentiate thalassaemia genotypes in pregnant women. In addition, combined with haemoglobin electrophoresis HbA2 can further distinguish the –α/αα, αTα/αα, –/αα, β+/N and β0/N groups. HbA2 divides them into two groups. Based on the Mentzer formula, we can further decide which type of thalassaemia to screen (α/β and the subgroups) for genotyping. Therefore, this simpler and more cost-effective workflow has great potential for application in screening pregnant women for thalassaemia carriers.Impact Statement What is already known on this subject? Currently, it is known that thalassaemia gene carriers have abnormal blood indicators. Many findings describe their important values in distinguishing thalassaemia and other blood diseases. They combined different metrics as an algorithm to distinguish thalassaemia and iron deficiency anaemia. Prenatal screening is an effective method to reduce the incidence of thalassaemia. The current main method is PCR. Due to technical and financial constraints, many backward places cannot use this technology. The necessity for prenatal screening for thalassaemia has been overlooked. What the results of this study add? Among these algorithms, Mentzer formula revealed differences in haematological parameters during pregnancy between normal individuals and thalassaemia carriers. Combining the HbA2, thalassaemia carriers can be distinguished from normal individuals, including –α/αα, αTα/αα, –/αα, β0/N and β+/N. What are the implications of these findings for clinical practice and/or further research? We provide another tool for these hospitals that donot have Hb electrophoresis test and PCR. Then the clinical doctor can get some evidence and suggest women go to another big hospital for essential tests. It is an excellent suggestion. In the future, we will collect more specific gene types and further investigate their potential relationship using these formulas