Health Technology Assessment to assess value of biomarkers in the decision-making process

Methodological guidelines and publications of benefit-risk assessment for health technology assessment: a scoping review

OBJECTIVES

To map the available methodological guidelines and documents for conducting and reporting benefit-risk assessment (BRA) during health technologies' life cycle; and to identify methodological guidelines for BRA that could serve as the basis for the development of a BRA guideline for the context of health technology assessment (HTA) in Brazil.

DESIGN

Scoping review.

METHODS

Searches were conducted in three main sources up to March 2023: (1) electronic databases; (2) grey literature (48 HTA and regulatory organisations) and (3) manual search and contacting experts. We included methodological guidelines or publications presenting methods for conducting or reporting BRA of any type of health technologies in any context of the technology's life cycle. Selection process and data charting were conducted by independent reviewers. We provided a structured narrative synthesis of the findings.

RESULTS

From the 83 eligible documents, six were produced in the HTA context, 30 in the regulatory and 35 involved guidance for BRA throughout the technology's life cycle. We identified 129 methodological approaches for BRA in the documents. The most commonly referred to descriptive frameworks were the Problem, Objectives, Alternatives, Consequences, Trade-offs, Uncertainty, Risk and Linked decisions and the Benefit-Risk Action Team. Multicriteria decision analysis was the most commonly cited quantitative framework. We also identified the most cited metric indices, estimation and utility survey techniques that could be used for BRA.

CONCLUSIONS

Methods for BRA in HTA are less established. The findings of this review, however, will support and inform the elaboration of the Brazilian methodological guideline on BRA for HTA.

TRIAL REGISTRATION NUMBER

https://doi.org/10.17605/OSF.IO/69T3V.

Prediction of atherosclerotic cardiovascular risk in early childhood

Atherosclerotic lesions are present even in very young individuals and therefore, risk stratification for cardiovascular (CV) disease should be implemented in childhood to promote early prevention strategies. In this review we critically appraise clinical, biochemical and genetic biomarkers available for pediatric clinical practice, which might be integrated to build effective algorithms to identify children at risk of future CV events. The first critical issue is to characterize in children aged 2-5 years, those CV risk factors/clinical conditions associated with dramatically accelerated atherosclerosis. Presence of clinical conditions such as obesity, diabetes mellitus, Kawasaki disease, etc., or positive family history for premature CV disease should be evaluated. Subsequently, a complete lipid profile and Lipoprotein(a) determination are recommended for children with increased baseline CV risk. Individuals with altered lipid profile could then undergo genetic testing for monogenic dyslipidemias to identify children with high CV genetic risk, who will be directed to appropriate therapeutic options. In perspective, calculation of a polygenic risk score, based on the analysis of several common single-nucleotide polymorphisms, could be integrated for better risk assessment. We here emphasize the importance of a "holistic" strategy integrating biochemical, anamnestic and genetic data to stratify CV risk in early childhood.

Toolkit for emerging technologies in laboratory medicine

An emerging technology (ET) for laboratory medicine can be defined as an analytical method (including biomarkers) or device (software, applications, and algorithms) that by its stage of development, translation into broad routine clinical practice, or geographical adoption and implementation has the potential to add value to clinical diagnostics. Considering the laboratory medicine-specific definition, this document examines eight key tools, encompassing clinical, analytical, operational, and financial aspects, used throughout the life cycle of ET implementation. The tools provide a systematic approach starting with identifying the unmet need or identifying opportunities for improvement (Tool 1), forecasting (Tool 2), technology readiness assessment (Tool 3), health technology assessment (Tool 4), organizational impact map (Tool 5), change management (Tool 6), total pathway to method evaluation checklist (Tool 7), and green procurement (Tool 8). Whilst there are differences in clinical priorities between different settings, the use of this set of tools will help support the overall quality and sustainability of the emerging technology implementation.

Striving for a pragmatic contribution of biomarkers results to lifelong health care

BACKGROUND

The increased role of preventive medicine in healthcare and the rapid technological advancements, have deeply changed the landscape of laboratory medicine. In particular, increased investments in newborn screening tests and policies have been observed. Aim of this paper is to characterize how laboratory professionals engaged in clinical chemistry or newborn screening, in collaboration with experts in econometric, bioinformatics, and biostatistics may address a pragmatic use of laboratory results in the decision-making process oriented toward improvement of health care outcomes.

CONTENT

The effectiveness of biomarkers on healthcare depends on several factors such as analytical performance, prevalence of the disease, integration of the test within the diagnostic algorithm, associated costs, and social/economic impact of false positive and false negative results. Cost-effectiveness analysis needs to be performed and reliability achieved, by overcoming analytical pitfalls and by improving interpretative criteria. These are challenging issues common to clinical chemistry and newborn screening tests. Following the experience in clinical chemistry, one of the main issues to be approached in newborn screening tests, is the lack of harmonization of results obtained by different methods and the limited healthcare effectiveness.

SUMMARY

The focus on prevention is a crucial opportunity for laboratory medicine to change how to approach the effectiveness of biomarkers on healthcare. The consolidation within clinical laboratories of professionals with different technical and methodological expertise coupled with the need to produce and manage large sets of data, require the cooperation of professionals from other disciplines to characterize the impact of the tests on epidemiological outcomes for health care policy making process.

Managing the impact of inter-method bias of prostate specific antigen assays on biopsy referral: the key to move towards precision health in prostate cancer management

OBJECTIVES

We assessed the inter-method bias of total (tPSA) and free (fPSA) prostate-specific antigen (PSA) immunoassays to establish if tPSA-based risk thresholds for advanced prostate cancer (PCa), obtained from one method (Roche) can be converted into the corresponding concentrations assayed by other methods. Then we evaluated the impact of the bias of tPSA and fPSA on the estimation of the %f/tPSA ratio and performed a re-calibration of the proposed thresholds for the %f/tPSA ratio according to the assay used.

METHODS

tPSA and fPSA were measured in 135 and 137 serum samples, respectively by Abbott Alinity i, Beckman Access Dxl, Roche Cobas e801, and Siemens Atellica IM analytical platforms. Scatterplots, Bland-Altman diagrams, Passing-Bablok (PB) were used to inspect and estimate the systematic and proportional bias between the methods. The linear equations with confidence intervals of the parameter estimates were used to transform the tPSA risk thresholds for advanced PCa into the corresponding concentrations measurable by the other analytical methods. To construct a correction coefficient for converting the %f/tPSA ratio from one method to the other, PB and non-parametric boostrapping were used.

RESULTS

The inter-method bias is not constant but strictly linear allowing the conversion of PSA results obtained from Roche into the other assays, which underestimate tPSA vs. Roche. Siemens and Abbott vs. Roche and Beckman assays, being characterized by a positive and a negative proportional bias for tPSA and fPSA measurements, tend to overestimate the %f/tPSA ratio.

CONCLUSIONS

There is a consistent risk to miss advanced PCa, if appropriate conversion factors are not applied.

Tutorial: statistical methods for the meta-analysis of diagnostic test accuracy studies

This tutorial shows how to perform a meta-analysis of diagnostic test accuracy studies (DTA) based on a 2 × 2 table available for each included primary study. First, univariate methods for meta-analysis of sensitivity and specificity are presented. Then the use of univariate logistic regression models with and without random effects for e.g. sensitivity is described. Diagnostic odds ratios (DOR) are then introduced to combine sensitivity and specificity into one single measure and to assess publication bias. Finally, bivariate random effects models using the exact binomial likelihood to describe within-study variability and a normal distribution to describe between-study variability are presented as the method of choice. Based on this model summary receiver operating characteristic (sROC) curves are constructed using a regression model logit-true positive rate (TPR) over logit-false positive rate (FPR). Also it is demonstrated how to perform the necessary calculations with the freely available software R. As an example a meta-analysis of DTA studies using Procalcitonin as a diagnostic marker for sepsis is presented.

From research cohorts to the patient - a role for "omics" in diagnostics and laboratory medicine?

Human pathologies are complex and might benefit from a more holistic diagnostic approach than currently practiced. Omics is a concept in biological research that aims to comprehensively characterize and quantify large numbers of biological molecules in complex samples, e.g., proteins (proteomics), low molecular weight molecules (metabolomics), glycans (glycomics) or amphiphilic molecules (lipidomics). Over the past decades, respective unbiased discovery approaches have been intensively applied to investigate functional physiological and pathophysiological relationships in various research study cohorts. In the context of clinical diagnostics, omics approaches seem to have potential in two main areas: (i) biomarker discovery i.e. identification of individual marker analytes for subsequent translation into diagnostics (as classical target analyses with conventional laboratory techniques), and (ii) the readout of complex, higher-dimensional signatures of diagnostic samples, in particular by means of spectrometric techniques in combination with biomathematical approaches of pattern recognition and artificial intelligence for diagnostic classification. Resulting diagnostic methods could potentially represent a disruptive paradigm shift away from current one-dimensional (i.e., single analyte marker based) laboratory diagnostics. The underlying hypothesis of omics approaches for diagnostics is that complex, multigenic pathologies can be more accurately diagnosed via the readout of "omics-type signatures" than with the current one-dimensional single marker diagnostic procedures. While this is indeed promising, one must realize that the clinical translation of high-dimensional analytical procedures into routine diagnostics brings completely new challenges with respect to long-term reproducibility and analytical standardization, data management, and quality assurance. In this article, the conceivable opportunities and challenges of omics-based laboratory diagnostics are discussed.

Fibroblast growth factor 23: translating analytical improvement into clinical effectiveness for tertiary prevention in chronic kidney disease

OBJECTIVES

Fibroblast growth factor 23 (FGF23) plays a key role in the pathophysiology of chronic kidney disease (CKD) and of the associated cardiovascular diseases, ranking on the crossroads of several evolving areas with a relevant impact on the health-care system (ageing, treatment of CKD and prevention from cardiovascular and renal events). In this review, we will critically appraise the overall issues concerning the clinical usefulness of FGF23 determination in CKD, focusing on the analytical performances of the methods, aiming to assess whether and how the clinical introduction of FGF23 may promote cost-effective health care policies in these patients.

CONTENT

Our comprehensive critical appraisal of the literature revealed that we are currently unable to establish the clinical usefulness of FGF23 measured by ELISA in CKD, as stability issues and suboptimal analytical performances are the major responsible for the release of misleading results. The meta-analytical approach has failed to report unambiguous evidence in face of the wide heterogeneity of the results from single studies.

SUMMARY AND OUTLOOK

Our review has largely demonstrated that the clinical usefulness depends on a thorough analytical validation of the assay. The recent introduction of chemiluminescent intact-FGF23 (iFGF23) assays licensed for clinical use, after passing a robust analytical validation, has allowed the actual assessment of preliminary risk thresholds for cardiovascular and renal events and is promising to capture the iFGF23 clinically relevant changes as a result of a therapeutic modulation. In this perspective, the analytical optimization of FGF23 determination may allow a marriage between physiology and epidemiology and a merging towards clinical outcomes.

Comprehensive analysis of nine m7G-related lncRNAs as prognosis factors in tumor immune microenvironment of hepatocellular carcinoma and experimental validation

Background: Hepatocellular carcinoma (HCC) remains the most prevalent gastrointestinal malignancy worldwide, with robust drug resistance to therapy. N7-methylguanosine (m7G) mRNA modification has been significantly related to massive human diseases. Considering the effect of m7G-modified long non-coding RNAs (lncRNAs) in HCC progression is unknown, the study aims at investigating a prognostic signature to improve clinical outcomes for patients with HCC.

Methods: Two independent databases (TCGA and ICGC) were used to analyze RNAseq data of HCC patients. First, co-expression analysis was applied to obtain the m7G-related lncRNAs. Moreover, consensus clustering analysis was employed to divide HCC patients into clusters. Then, using least absolute shrinkage and selection operator-Cox regression analysis, the m7G-related lncRNA prognostic signature (m7G-LPS) was first tested in the training set and then confirmed in both the testing and ICGC sets. The expression levels of the nine lncRNAs were further confirmed via real-time PCR in cell lines, principal component analysis, and receiver operating characteristic curve. The m7G-LPS could divide HCC patients into two different risk groups with the optimal risk score. Then, Kaplan–Meier curves, tumor mutation burden (TMB), therapeutic effects of chemotherapy agents, and expressions of immune checkpoints were performed to further enhance the availability of immunotherapeutic treatments for HCC patients.

Results: A total of 1465 lncRNAs associated with the m7G genes were finally selected from the TCGA database, and through the univariate Cox regression, the expression levels of 22 m7G-related lncRNAs were concerning HCC patients’ overall survival (OS). Then, the whole patients were grouped into two subgroups, and the OS in Cluster 1 was longer than that of patients in Cluster 2. Furthermore, nine prognostic m7G-related lncRNAs were identified to conduct the m7G-LPS, which were further verified. A prognostic nomogram combined age, gender, HCC grade, stage, and m7G-LPS showed strong reliability and accuracy in predicting OS in HCC patients. Finally, immune checkpoint expression, TMB, and several chemotherapy agents were remarkably associated with risk scores. More importantly, the OS of the TMB-high patients was the worst among the four groups.

Conclusion: The prognostic model we established was validated by abundant algorithms, which provided a new perspective on HCC tumorigenesis and thus improved individualized treatments for patients.

The novelties of the regulation on health technology assessment, a key achievement for the European union health policies

Health technology assessment is a key tool for ensuring healthcare quality, accessibility, and sustainability. The novel European Union (EU) Health Technology Assessment (HTA) regulation of 15 December 2021, in harmonizing the laws of the Member States about the procedures and criteria for the evaluation of health technologies (i.e., medical devices and in vitro diagnostic tools), constitutes a significant achievement in the definition of EU health policies. On the one hand, for the European Union, it constitutes an essential driving force for the development of a competitive market for health technologies and, on the other, for European citizens, it guarantees the application of superordinate safety and quality standards with an impact positive on access to health technologies, including expressly also in vitro diagnostic medical devices classified in class D by art. 47 of Reg. (EU) 2017/746. As pointed out by the European Commissioner for Healthcare, the regulation identifies a new way for the Member States to cooperate on healthcare matters in the Union. The clinical efficacy and safety of drugs and devices are legal assets that today find their protection in a binding and directly applicable regulatory instrument, superordinate in the hierarchy of sources. Implementing the regulation will also be essential to achieve the objectives of the Union's pharmaceutical strategy and the European plan to fight cancer. The novel HTA European regulation, applicable from January 2025, will ensure inclusion and transparency in evaluating health technologies and increase the predictability of decisions for both Member State authorities and industry.