Utility of polygenic risk scores in UK cancer screening: a modelling analysis

Huntley, Catherine; Torr, Bethany; Sud, Amit; Rowlands, Charlie F.; Way, Rosalind; Snape, Katie; Hanson, Helen; Swanton, Charles; Broggio, John; Lucassen, Anneke; McCartney, Margaret; Houlston, Richard S.; Hingorani, Aroon D.; Jones, Michael E.; Turnbull, Clare

doi:10.1016/s1470-2045(23)00156-0

Cited by 42 publications

(23 citation statements)

References 18 publications

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“…This is consistent with previous studies, which have shown that risk stratification can main the benefits of screening for breast and colorectal cancer. 4 , 33 , 36 Besides, our study also first proved that PRS-stratified risk stratification is a cost-effective approach for gastric, oesophageal and lung cancer screening. Despite China’s substantial burden of liver cancer, PRS-stratified screening for liver cancer is unlikely to be considered a feasible approach in this country.…”

Section: Discussionsupporting

confidence: 56%

“…The odds ratio for cancer of PRS-defined 25% high-risk quantiles were informed from population-based cohort studies in Chinese populations, 9 , 22 , 23 , 24 , 25 , 26 and the proportion of high-risk individuals in PRS-based risk assessment was estimated by assuming PRS follow a Gaussian distribution in populations. 4 Uptake rates of clinical screening, and risks of complications associated with screening tests were extracted from the cancer screening programme. The sensitivity and specificity of the screening tests were based on the diagnostic test accuracy studies.…”

Section: Methodsmentioning

confidence: 99%

“…3 The health impact of cancer screening is predicated on multiple factors, including cancer incidence, natural history of cancer progression, performances of screening modalities, and screening-related harms. 4 Tailoring screening to an individual’s risk level could improve the efficiency of the screening programmes and reduce its harms. 5 , 6 , 7 , 8 …”

Section: Introductionmentioning

confidence: 99%

“… 9 , 10 It is proposed that PRSs might enable more efficient targeting of existing cancer screening programmes in the United Kingdom. 4 However, risk-stratified screening would require assessing the risk of all populations, which would entail additional costs. Whether these incremental costs could be balanced by potential gains in yields like quality-adjusted life-years (QALYs) saved is a crucial issue that determines the feasibility of PRS application in the population.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Benefits and harms of polygenic risk scores in organised cancer screening programmes: a cost-effectiveness analysis

Xia,

Xu,

et al. 2024

The Lancet Regional Health - Western Pacific

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Section: Discussionsupporting

confidence: 56%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Benefits and harms of polygenic risk scores in organised cancer screening programmes: a cost-effectiveness analysis

Xia,

Xu,

et al. 2024

The Lancet Regional Health - Western Pacific

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“…From our analyses, using the PRS-based risk subgroup alone resulted in the lowest AUC, and including other non-genetic factors of age, gender, and smoking history largely improved the lung cancer risk prediction performance. PRS stand-alone is imperfect and the use of PRS as a covariate or effect modifier in conjunction with non-genetic risk factors may inform better outcomes [ 22 , 38 ]. Despite modest improvement in prediction accuracy using PRS-based risk subgroups taking individual-level uncertainty into account, likely due to the limited sample sizes of eligible individuals, it attains both PRS stability and predictive accuracy given the data.…”

Section: Discussionmentioning

confidence: 99%

Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification

Wang,

Zhang,

Ding

et al. 2024

Genome Med

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Background Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored. Methods Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold. Results Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12–3.50, P-value = 4.13 × 10−15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99–2.49, P-value = 5.70 × 10−46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72–0.74). Conclusions Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.

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Early Prostate Cancer Deaths Among Men With Higher vs Lower Genetic Risk

Plym,

Zhang,

Stopsack

et al. 2024

JAMA Netw Open

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ImportanceProstate cancer, a leading cause of cancer death among men, urgently requires new prevention strategies, which may involve targeting men with an underlying genetic susceptibility.ObjectiveTo explore differences in risk of early prostate cancer death among men with higher vs lower genetic risk to inform prevention efforts.Design, Setting, and ParticipantsThis cohort study used a combined analysis of genotyped men without prostate cancer at inclusion and with lifestyle data in 2 prospective cohort studies in Sweden and the US, the Malmö Diet and Cancer Study (MDCS) and the Health Professionals Follow-Up Study (HPFS), followed up from 1991 to 2019. Data were analyzed between April 2023 and April 2024.ExposuresMen were categorized according to modifiable lifestyle behaviors and genetic risk. A polygenic risk score above the median or a family history of cancer defined men at higher genetic risk (67% of the study population); the remaining men were categorized as being at lower genetic risk.Main Outcomes and MeasuresProstate cancer death analyzed using time-to-event analysis estimating hazard ratios (HR), absolute risks, and preventable deaths by age.ResultsAmong the 19 607 men included for analysis, the median (IQR) age at inclusion was 59.0 (53.0-64.7) years (MDCS) and 65.1 (58.0-71.8) years (HPFS). During follow-up, 107 early (by age 75 years) and 337 late (after age 75 years) prostate cancer deaths were observed. Compared with men at lower genetic risk, men at higher genetic risk had increased rates of both early (HR, 3.26; 95% CI, 1.82-5.84) and late (HR, 2.26; 95% CI, 1.70-3.01) prostate cancer death, and higher lifetime risks of prostate cancer death (3.1% vs 1.3% [MDCS] and 2.3% vs 0.6% [HPFS]). Men at higher genetic risk accounted for 94 of 107 early prostate cancer deaths (88%), of which 36% (95% CI, 12%-60%) were estimated to be preventable through adherence to behaviors associated with a healthy lifestyle (not smoking, healthy weight, high physical activity, and a healthy diet).Conclusions and RelevanceIn this 20-year follow-up study, men with a genetic predisposition accounted for the vast majority of early prostate cancer deaths, of which one-third were estimated to be preventable. This suggests that men at increased genetic risk should be targeted in prostate cancer prevention strategies.

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Utility of polygenic risk scores in UK cancer screening: a modelling analysis

Cited by 42 publications

References 18 publications

Benefits and harms of polygenic risk scores in organised cancer screening programmes: a cost-effectiveness analysis

Benefits and harms of polygenic risk scores in organised cancer screening programmes: a cost-effectiveness analysis

Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification

Early Prostate Cancer Deaths Among Men With Higher vs Lower Genetic Risk

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