Background/Objectives: Non-Hodgkin lymphoma (NHL) represents 63% of all hematological malignancies in France, with diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) being the two most frequent forms. With the improvement of therapeutics, the issue of health-related quality of life (HRQoL) is becoming increasingly crucial for these patients. The aim was to compare HRQoL of NHL survivors with that of the general French population and to identify factors associated with HRQoL in NHL survivors. Methods: We conducted a population-based study among living patients from three registries of hematological malignancies, using standardized questionnaires, including the SF-12, in September 2023. The data collected were compared to those of a normative general French cohort. Results: In total, 493 patients completed the study questionnaires, yielding a response rate of 36%. The median time since diagnosis was 8 years (IQR 6–10) These NHL survivors reported lower HRQoL compared to the general French population, except in terms of bodily pain (p < 0.01). Each one-year increase in the time since diagnosis was associated with an increase in social functioning (p = 0.009). Men had better general health (p = 0.01) and less bodily pain (p = 0.007) than women. Higher income was associated with better HRQoL (p < 0.01). Underweight or obesity were associated with poorer physical functioning (p = 0.008). The presence of comorbidities, socioeconomic deprivation, anxiety, and depression were associated with poorer HRQoL (p < 0.01). Conclusions: This study provides valuable information of HRQoL values for comparison in further follow-up studies and proposes measures that could be implemented to improve the HRQoL of NHL survivors.

Targeted therapies have greatly improved cancer patient prognosis. For instance, chronic myeloid leukemia is now well treated with imatinib, a tyrosine kinase inhibitor. Around 80% of the patients reach complete remission. However, despite its great efficiency, some patients are resistant to the drug. This heterogeneity in the response might be associated with pharmacokinetic parameters, varying between individuals because of genetic variants. To assess this issue, next-generation sequencing of large panels of genes can be performed from patient samples. However, the common problem in pharmacogenetic studies is the availability of samples, often limited. In the end, large sequencing data are obtained from small sample sizes; therefore, classical statistical analyses cannot be applied to identify interesting targets. To overcome this concern, here, we described original and underused statistical methods to analyze large sequencing data from a restricted number of samples. To evaluate the relevance of our method, 48 genes involved in pharmacokinetics were sequenced by next-generation sequencing from 24 chronic myeloid leukemia patients, either sensitive or resistant to imatinib treatment. Using a graphical representation, from 708 identified polymorphisms, a reduced list of 115 candidates was obtained. Then, by analyzing each gene and the distribution of variant alleles, several candidates were highlighted such as UGT1A9, PTPN22, and ERCC5. These genes were already associated with the transport, the metabolism, and even the sensitivity to imatinib in previous studies. These relevant tests are great alternatives to inferential statistics not applicable to next-generation sequencing experiments performed on small sample sizes. These approaches permit to reduce the number of targets and find good candidates for further treatment sensitivity studies.