A systematic review of the methodological quality of economic evaluations in genetic screening and testing for monogenic disorders

PurposeUnderstanding the value of genetic screening and testing for monogenic disorders requires high-quality, methodologically robust economic evaluations. This systematic review sought to assess the methodological quality among such studies and examined opportunities for improvement.MethodsWe searched PubMed, Cochrane, Embase, and Web of Science for economic evaluations of genetic screening/testing (2013-2019). Methodological rigor and adherence to best practices were systematically assessed using the British Medical Journal checklist.ResultsAcross the 47 identified studies, there were substantial variations in modeling approaches, reporting detail, and sophistication. Models ranged from simple decision trees to individual-level microsimulations that compared between 2 and >20 alternative interventions. Many studies failed to report sufficient detail to enable replication or did not justify modeling assumptions, especially for costing methods and utility values. Meta-analyses, systematic reviews, or calibration were rarely used to derive parameter estimates. Nearly all studies conducted some sensitivity analysis, and more sophisticated studies implemented probabilistic sensitivity/uncertainty analysis, threshold analysis, and value of information analysis.ConclusionWe describe a heterogeneous body of work and present recommendations and exemplar studies across the methodological domains of (1) perspective, scope, and parameter selection; (2) use of uncertainty/sensitivity analyses; and (3) reporting transparency for improvement in the economic evaluation of genetic screening/testing.     

Living with the financial consequences of cancer: A life course perspective

Abstract

Purpose

Financial hardship can be a major cause of distress among persons with cancer, resulting in chronic stress and impacting physical and emotional health. This paper provides an analysis of the lived experience of cancer patients’ financial hardship from diagnosis to post-treatment.     

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

Can EGFR mutation status be reliably determined in pre‐operative needle biopsies from adenocarcinomas of the lung?

The identification of EGFR mutations in non‐small‐cell lung cancer is important for selecting patients, who may benefit from treatment with EGFR tyrosine kinase inhibitors. The analysis is usually performed on cytological aspirates and/or histological needle biopsies, representing a small fraction of the tumour volume. The aim of the present investigation was to evaluate the diagnostic performance of this molecular test. We retrospectively included 201 patients with primary adenocarcinoma of the lung. EGFR mutation status (exon 19 deletions and exon 21 L858R point mutation) was evaluated on both pre‐operative biopsies (131 histological and 70 cytological) and on the surgical specimens, using PCR. Samples with low tumour cell fraction were assigned to laser micro‐dissection (LMD). We found nine (4.5%) patients with EGFR mutation in the lung tumour resections, but failed to identify mutation in one of the corresponding pre‐operative, cytological specimens. Several (18.4%) analyses of the pre‐operative biopsies were inconclusive, especially in case of biopsies undergoing LMD and regarding exon 21 analysis. Discrepancy of mutation status in one patient may reflect intra‐tumoural heterogeneity or technical issues. Moreover, several inconclusive results in the diagnostic biopsies reveal that attention must be paid on the suitability of pre‐operative biopsies for EGFR mutation analysis.