Next-Generation Sequencing in Clinical Practice: Is It a Cost-Saving Alternative to a Single-Gene Testing Approach?

Abstract

Objectives: This study aimed to compare the costs of a next-generation sequencing-based (NGS-based) panel testing strategy to those of a single-gene testing-based (SGT-based) strategy, considering different scenarios of clinical practice evolution.

Methods: Three Italian hospitals were analysed, and four different testing pathways (paths 1, 2, 3, and 4) were identified: two for advanced non-small-cell lung cancer (aNSCLC) patients and two for unresectable metastatic colon-rectal cancer (mCRC) patients. For each path, we explored four scenarios considering the current clinical practice and its expected evolution. The 16 testing cases (4 scenarios × 4 paths) were then compared in terms of differential costs between the NGS-based and SGT-based approaches considering personnel, consumables, equipment, and overhead costs. Break-even and sensitivity analyses were performed. Data gathering, aimed at identifying the hospital setup, was performed through a semi-structured questionnaire administered to the professionals involved in testing activities.

Results: The NGS-based strategy was found to be a cost-saving alternative to the SGT-based strategy in 15 of the 16 testing cases. The break-even threshold, the minimum number of patients required to make the NGS-based approach less costly than the SGT-based approach, varied across the testing cases depending on molecular alterations tested, techniques adopted, and specific costs. The analysis found the NGS-based approach to be less costly than the SGT-based approach in nine of the 16 testing cases at any volume of tests performed; in six cases, the NGS-based approach was found to be less costly above a threshold (and in one case, it was found to be always more expensive). Savings obtained using an NGS-based approach ranged from €30 to €1249 per patient; in the unique testing case where NGS was more costly, the additional cost per patient was €25.

Conclusions: An NGS-based approach may be less costly than an SGT-based approach; also, generated savings increase with the number of patients and different molecular alterations tested.

Fig. 1

Research design. Two testing pathways for each of the diseases considered (paths 1 and 2 for aNSCLC and paths 3 and 4 for mCRC) were investigated in three Italian hospitals. Four scenarios (“minimum set”, “clinical practice” (CP), “future CP no TMB”, and “future CP”) were defined for each testing pathway, and cost analyses were conducted comparing the SGT-based and NGS-based approaches for each of the 16 testing cases identified. aNSCLC advanced non-small-cell lung cancer, CP clinical practice, mCRC metastatic colon-rectal cancer, NGS next-generation sequencing, SGT single-gene testing, TMB tumour mutational burden, vs versus

Fig. 2

Mean cost per patient. The mean cost per patient comparing the SGT-based and NGS-based approaches is shown for each testing case considering personnel, consumables, equipment (purchasing and maintenance), and overhead costs to perform all the required tests. aNSCLC advanced non-small-cell lung cancer, CP clinical practice, mCRC metastatic colon-rectal cancer, NGS next-generation sequencing, SGT single-gene testing, TMB tumour mutational burden

Fig. 3

∆_SGT→NGS overall personnel time savings. The overall personnel time savings generated by the NGS-based approach are shown for each testing case. aNSCLC advanced non-small-cell lung cancer, CP clinical practice, mCRC metastatic colon-rectal cancer, NGS next-generation sequencing, SGT single-gene testing, TMB tumour mutational burden

Fig. 4

Break-even analysis (path 3). The mean cost per patient for the SGT-based and NGS-based approaches in path 3 is displayed for each scenario and reported as a function of patient volume. The number of patients tested by the hospital (“volume path 3”) and the threshold necessary for the NGS-based approach to generate savings (“break-even”) are shown. CP clinical practice, NGS next-generation sequencing, SGT single-gene testing, TMB tumour mutational burden

Fig. 5

Deterministic sensitivity analysis (CP scenario). The results of the DSA are shown in the CP scenario and are displayed in a tornado diagram (the 15 most impactful variables are included). Input data were varied (± 20%), and impacts on the ∆_SGT→NGS savings were observed. CP clinical practice, DSA deterministic sensitivity analysis, FISH fluorescence in situ hybridization, IHC immunohistochemistry, ISH in situ hybridization, mCRC metastatic colon-rectal cancer, NGS next-generation sequencing, RT-PCR real-time polymerase chain reaction, SGT single-gene testing, TMB tumour mutational burden, ∆_SGT→NGS variation in the transition from an SGT-based approach to an NGS-based approach