Background: Chronic lymphocytic leukaemia (CLL) represents a clinically heterogeneous, lymphoproliferative neoplasm resulting in chronic B-lymphocyte proliferation. Historically, large cytogenetic aberrations detected by fluorescent in situ hybridisation were identifiable in patients, enabling prognostic assessment. With the development of next generation sequencing (NGS), variants have been identified in several genes that are recurrently mutated in CLL, including TP53, ATM, BIRC3, NOTCH1 and SF3B1, with the prognostic implications of variants in these genes being reported. However, only TP53 variant status has been incorporated into routine clinical diagnostics to guide prognosis, risk stratification and appropriate therapeutic interventions based on findings indicating decreased survival and resistance to immunochemotherapy. Aims: The aims of this study were to assess NGS gene panel content and design approaches in CLL to determine levels of harmonisation amongst laboratories. Methods: The United Kingdom National External Quality Assessment Service for Leucocyte Immunophenotyping has provided external quality assessment for use of NGS technologies in CLL since 2018. The programme routinely requests NGS panel information (gene content and exon coverage) and other methodological data from participating laboratories. Data returns from 2018-2021 relating to NGS gene content and panel analysis were evaluated. Results: In total, 127 genes were analysed across 34 laboratories, ranging from 1-82 genes analysed in the context of CLL per laboratory (median of 12 genes). Of the 34 laboratories evaluated, five analysed TP53 only, with four of these utilising a non-disease specific myeloid NGS panel. The most commonly analysed genes were TP53 (100% laboratories), SF3B1 (73.5%) and NOTCH1 (70.6%). For these genes, there was a high-level of standardisation in sequencing approaches; with 91.2% of laboratories sequencing coding exons 2-11 in TP53 and 100% laboratories sequencing ‘hotspot’ exon 34 of NOTCH1, accounting for >80% variants in NOTCH1 associated with CLL. For SF3B1, 87% laboratories sequenced exons 14-16, which are hotspots for variants. Other frequently analysed genes included MYD88 (61.8% laboratories), BTK (58.8%), ATM and PLCG2 (52.9%). Summary/Conclusion: The number of genes analysed in the context of CLL amongst laboratories was highly variable. Use of NGS genetic testing approaches in haemato-oncology aids in accurate diagnosis and prognosis, however, the cost of developing these panels is not insubstantial and as such, laboratories often design panels to encompass multiple lymphoid/haematological neoplasms. Whilst recommendations outline the need for TP53 testing in CLL, the lack of technical and clinical guidelines on minimal NGS panel content and bioinformatic analysis that provide additional prognostic information has resulted in a wide variation in bioinformatic analysis approaches. This inevitably results in wide disparity of data generated and subsequent clinical interpretation. Guidelines are urgently needed for the identification of minimal NGS panel content in CLL and in other mature lymphoid neoplasms, outlining key genes directly involved in the diagnostic, prognostic and theranostic outputs in order to standardise patient testing and care.