20 e-Letters

  • Scrutinizing the potential of personalized nutrition for precision cardiometabolic health in diabetes care

    The umbrella review by the research team of Szczerba and colleagues offers a perspective of the potential of scrutinizing the utility of personalized nutrition for impacting type 2 diabetes management and is a contribution to the field. By synthesizing evidence from RCTs that lasted at least 12 weeks, the authors not only attempt to offer a robust assessment of various dietary interventions, but also employ strict methodological rigor through the re-calibration of meta-analyses and application of the GRADEpro approach.

    One of the work’s strengths lies in its comprehensive scope, meticulously evaluating the certainty of evidence and identifying gaps for future research. This approach not only signals the reliability of findings due to rigor and quality of studies, but also shows a way to scrutinize the potential of personalized nutrition strategies.

    Although authors state and acknowledge limitations, such as the exclusion of the most recent RCTs and the absence of subgroup and sensitivity analyses, which could refine the study’s conclusions further, the study stands out for its dedication to precision and methodological excellence and voluminous work, offering valuable insights into the complex relationship between diet and type 2 diabetes management.

    Findings underscore the importance of personalized nutrition in managing cardiometabolic health, exploring new standards for future studies in this vital area. It’s a significant step forward in our unders...

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  • Joint reply to Rice and colleagues and Lambert and colleagues

    We address points made in the two letters written by Rice, Lambert, and their colleagues.

    Point 1: Unrealistic premise / Confuses clinical researchers and the public.
    We show that polygenic risk scores are poor predictors of disease whether used alone (as they are in direct-to-consumer genetic tests and have been in previous publications), or in combination with other risk factors [1]. If they perform poorly on their own, as we show, they cannot have useful incremental value when used with other risk factors, as we also show. Use of the appropriate metrics, as we employed in our paper, clarifies the position; it is the use of inappropriate metrics that causes needless confusion.

    Point 2: Multifactorial models incorporating PRS improve risk prediction and are cost effective.
    Any potential screening marker that offers negligible screening performance when used alone or in a risk model cannot be cost effective. In the case of cardiovascular disease, risk factor models offer poor discrimination, with or without polygenic risk scores. Table 1 in our paper [1] shows that over 5000 people need to be genotyped to prevent one additional cardiovascular event. The cost-effectiveness analysis cited by the correspondents [2] did not compare the effectiveness of a multi risk factor model based strategy with alternatives such as an aged based strategy [3]. All risk models (with or without polygenic risk scores) add cost and impose a barrier to accessing ef...

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  • PGS study starts from unrealistic premise

    Dear Editor,

    Hingorani et al state that their mathematical modeling of published performance metrics of polygenic scores (PGS) demonstrates that PGS
    have poor clinical value. However, their conclusions are based on incomplete premises and do not account for clinical context. We believe their publication does not advance the debate regarding potential PGS clinical utility and may confuse clinical researchers and the public.

    The premise that PGS are stand-alone screening tools omits the routine use of other important risk factors in clinical decision-making. To illustrate by example, if serum cholesterol levels are used alone, they fail to predict CVD outcomes with the accuracy of, say, maternal serum alpha fetoprotein for detecting spina bifida [1]. But serum cholesterol levels are not used alone: 60 years of work on multifactorial cardiovascular risk models for prediction and targeting preventative therapies is integrated into the Framingham risk score, QRISK2/3, and clinical guidelines worldwide [2]. In all of these, serum cholesterol plays a useful role even though most cases of heart attack among those not on a statin have serum cholesterol in the normal range [3]. As part of integrated risk scores, PGS have already been widely shown to improve CVD prediction [4–6] as well as tailor screening approaches for breast cancer risk [7]. Hingorani et al's evaluations do not consider using integrated risk scores that include PGS, family history, environ...

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  • Realistic evaluations of polygenic risk scores show potential utility

    Hingorani et al conduct population modelling to conclude that polygenic risk scores (PRS) perform poorly in population screening, individual risk prediction, and population risk stratification. Unfortunately, their framework is flawed and inappropriately predicated on the use of PRS as a standalone diagnostic test. We argue that their results misrepresent the potential use cases for PRS, and we highlight studies showing utility and cost-effectiveness of PRS.

    PRS are neither diagnostic nor standalone risk factors. Hingorani et al evaluate the use of PRS with a metric commonly used for diagnostic tests - detection rate for a 5% false positive rate (DR5). However, it is well-recognised that PRS are continuous risk predictors[1], not diagnostic tests. For example, mammograms are offered to all women aged 50-69 every three years in the UK. If we evaluate age as the screening test, 8,191 of a cohort of 100,000 UK women would be invited each year to mammogram screening.[2] Of these, 54 would have screen-detected cancer, giving a 99% false positive rate for age-based screening, and 111 breast cancers would be missed in the 91,698 unscreened women, giving a 67% false negative rate.[3,4] Neither age nor PRS are screening tests per se: rather, they define a population in whom screening would be of greatest benefit. Therefore, the authors’ analyses are more specifically critiques of screening tests and not the utility of PRS. Combining age with PRS could improve the efficiency...

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  • How other strategies to tackle long covid shouldn't be ignored and why it is important to demonstrate an established evidence of vaccine helping control symptoms in patients of long covid?

    The article very clearly demonstrates how different research papers show varying results regarding the effect of covid vaccine in controlling symptoms of long covid. Many factors were mentioned that potentially show the limitations in providing appropriate evidence to prove that vaccine helps improve the health of patients suffering from long covid. However, several factors weren't mentioned. The psychogenic element of stigmatization after being infected with covid which may be an individualised experience is not mentioned. The effect of lifestyle including diet, exercise, pursuing medical care, and rehabilitation programs is also not mentioned while they may be important factors in controlling the effects of these symptoms.
    Several other strategies are usually used in tackling symptoms of many post-viral syndromes. It remains important to link and relate long covid to other post-viral syndromes and evaluate the effect of different medical and non-medical strategies to control such symptoms. The ultimate goal remains to escalate the health status of long covid patients and not merely show an advantageous effect of covid vaccine in such cases.
    Post viral fatigue syndrome is an important example to consider in such cases as the symptoms spectrum differs with factors such as lifestyle, diet, exercise, habits of smoking or drinking alcohol, and psychogenic support systems. Similarly, long covid may also be linked to such factors.
    In the new era of socia...

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  • Performance of polygenic risk scores in screening, prediction, and risk stratification - reply to rapid responses

    Reply to rapid responses
    Contrary to Padrik and colleagues assertion, we did examine polygenic risk scores for coronary artery disease and breast cancer together with conventional risk factors and screening tests (see Table 1 and Figure 7 of the paper) [1]. We showed that, among women aged 50, a polygenic risk score above the 95th or 97.5th centiles had minimal value in screening. Padrik and colleagues question the use of the 97.5th centile, because it detects only 6% of cases. Selecting the 80th centile instead, the detection rate would be higher at 32% (68% of cases missed) but so would the false positive rate (20%), giving a likelihood ratio of only 1.5, which is poor screening performance.

    Both Padrik and colleagues, and Evans, refer to the fourfold gradient of risk across the range of polygenic risk scores for breast cancer and infer clinical utility. As has been shown before [2–4], and in our paper, much higher relative risk differences are needed to achieve worthwhile medical screening. Padrik and colleagues and Evans envisage polygenic risk scores being used in combination with other risk factors, but such an addition confers a very small improvement in screening performance, as previously reported and explained [5].

    Evans’ analysis of women attending for mammography as part of the PROCAS study [6] can be reduced to the TC8-DR-SNP313 risk model incorporating polygenic risk scores identifying 42% (144/340) of interval breast cancers among wom...

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  • Bird's eye view misses the benefits of customised assessment

    Kilpi and colleagues’ [1] comparative analysis of databases from the UK and several Nordic countries concluded that the benefits of customised vs population based standards for determining SGA are limited when assessing risk of stillbirth and other adverse outcomes.

    Regrettably their approach was unlikely to be able to elucidate the advantages of a customised standard. For each country’s cohort, the authors compared adverse outcomes for the lowest 10% of pregnancies by weight-for-gestation. Because of the strong association between SGA and outcomes such as stillbirth [2], this is where most at-risk pregnancies and adverse outcomes will be found, regardless of the standard used. We illustrated this in a comparative analysis of customised GROW and 3 other fetal weight standards (see table 2 in [3]): the relative risk for stillbirth was essentially the same for each standard, and customisation had little effect. The same would apply to the country cohorts in Kilpi et al [1].

    The fact that customisation adds little at country level has already been shown some time ago in the (not referenced) study from 24 countries [4], which combined population average birthweights with the proportionality equation we had developed for GROW. This approach can be useful in providing country specific charts where more data are not available, and ought to be supported [5]. However when there is more detailed information, the focus ought to be on subgroups of the population fo...

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  • Breast Cancer Polygenic Risk Scores Have Satisfactory Performance and Clear Clinical Utility

    The authors analysed performance metrics for 926 polygenic risk scores (PRSs) for 310 diseases (1). To assess the potential clinical impact of PRSs, it is essential to analyse each disease separately within its specific clinical context. The authors examine coronary artery disease and breast cancer as illustrative examples, but not in the full context of current prevention and screening approaches which are far from perfect. PRSs are not the primary screening methods for diseases; instead, they are supplementary tools that enhance disease risk assessment.
    The UK NHS Breast Screening Program offers routine screening to women between the ages of 50 and 70. Accordingly, risk stratification for screening uses age as a risk factor only. Independent UK Panel on Breast Cancer Screening concluded that a relative risk reduction from screening was 20%, for 10,000 women invited to screening, from age 50 for 20 years, it is estimated that 681 cancers will be diagnosed, of which 129 will represent overdiagnosis and 43 deaths from breast cancer will be prevented (2). We can say the vast majority of women are screened without any benefit but with harms. On the other side, 18% of breast cancer cases are diagnosed among women younger than age 50, they never reach screening (3). The authors state that reducing the age cut-off value for mammography for all women without determining their PRS might be more sensible. However, this non-risk-stratified approach makes screening even more no...

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  • Response to: Performance of polygenic risk scores in screening, prediction, and risk stratification: secondary analysis of data in the Polygenic Score Catalog and press release

    Hingorani et al {1] purport to show that polygenic risk scores (PRS) are not fit for purpose as they ‘performed poorly in population screening, individual risk prediction, and population risk stratification.’ Using breast cancer as one of two examples they use a PRS to show 10-year odds of becoming affected for individuals aged 50 with a polygenic risk score at the 2.5th, 25th, 75th, and 97.5th centiles were 1:91, 1:56, 1:34, and 1:21 for breast cancer with the upper 2.5% of the distribution, contributing 6% of cases. Many other known risk factors are easily available and can be used alongside a PRS in existing risk models such as CanRisk and Tyrer-Cuzick. Their assertions about not using a PRS are tantamount to saying you should not use any risk factor information to assess risk. A woman with a PRS of 2-fold will be at average risk if she has no family history of breast cancer and early first pregnancy and late menarche. Using other risk factors would substantially reduce the ‘false positives’ alluded to in the article as well as identifying more at true ‘high risk’. We have shown that using all available risk information including standard risk factors age and mammographic density as well as a PRS that 43.5% of breast cancers in women of screening age can be identified in 19.9% of the population at ≥5% 10-year risk in women of screening age (46-73years) [2]. Using the NICE defined 10-year threshold of ≥5% was also able to identify 48.5% of all stage 2 or higher cancers....

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  • Dr.

    The poor epidemiological performance of polygenic risk scores, as outlined in this paper, is not a reason to dismiss the consideration of such tests. We know that it is only by a comparative assessment to other risk assessment approaches (and even in addition to other risk assessment approaches) can a decision be reached as to whether polygenic risk tests are worthwhile use of NHS resources. So what remains to be done is an evaluation of whether the costs associated with genetic testing are justified considering the additional improvement in risk assessment performance. Even evidence from an economic evaluations in this area do not alone constitute definitive proof of the merits of polygenic risk assessment. This is because the economic advantages of added enhancement in risk assessment accuracy are closely linked to the economic benefits from screening programs provided to individuals at varying risk levels, as well as the number of risk groups in the population, factors that are independent of the accuracy of polygenic risk scores.