Risk-based screening programmes for cancer diagnosis: A systematic review with narrative synthesis

ABSTRACT

Introduction: Risk-based screening (RBS) has emerged as a promising alternative to age-based cancer screening. However, evidence regarding real-world implementation outcomes remains fragmented. Thus, a systematic review was conducted to evaluate the implementation methodologies and outcomes of RBS programmes across different cancer types.

Methods: MEDLINE, Embase, CINAHL, Web of Science, Cochrane Central Register of Controlled Trials and Scopus were systematically searched from their respective dates of inception up to 8 July 2024. Prospective and randomised controlled trials (RCTs), which implement the RBS of cancer in an asymptomatic population, or studies retrospectively evaluating the outcomes of the same were included. Geographic distribution, population characteristics, RBS methodology, diagnostic accuracy and clinical outcomes were narratively synthesised.

Results: Among the 33 included studies (i.e. 21 prospective cohort, 8 RCTs, 3 retrospective and 1 non-RCT), sample sizes ranged from 102 to 1,429,890 participants. Most RBS trials were conducted in China (n=7, 21.2%), followed by the Netherlands (n=4, 12.1%) then the US, Australia and Sweden (n=3, 9.8%). Studies predominantly examined colorectal (27.3%), breast (21.2%) and prostate cancer (18.2%). Three main stratification approaches emerged: algorithmic (48.5%), validated risk models (39.4%) and physician assessment (9.1%). Implementation outcomes showed higher uptake in moderate-risk (75.4%) compared to high-risk (71.3%) and low-risk groups (67.9%). Five studies demonstrated cost-effectiveness with increased quality-adjusted life years, while 12 studies showed superior or non-inferior cancer detection rates compared to traditional screening.

Conclusion: The RBS of cancer has the potential to optimise healthcare resource allocation while minimising harm and increasing receptiveness for patients. More work is needed to evaluate long-term outcomes prior to the scaling of RBS programmes.

CLINICAL IMPACT

What is New

• Risk-based screening (RBS), an emerging approach for the early detection of cancer, can lead to superior or non-inferior cancer detection rates compared to traditional screening with better cost-effectiveness and patient acceptability.

• Effective programmes were documented for common cancers, such as breast and cervical cancer, across different geographical regions.

Clinical Implications

• RBS can potentially optimise healthcare resource allocation while minimising harms from unnecessary screening.

• Long-term outcomes from large-scale programmes and participant experiences need to be evaluated before widespread RBS implementation.

Cancer remains one of the most significant public health burdens, with almost 20 million new cases and 9.7 million deaths attributable to cancer in 2022.¹ The detection and diagnosis of cancer remain a challenge for clinicians, as approximately half of recorded cancers are only detected at the advanced stage.^2,3 Late cancer diagnoses often translate to poor patient prognosis and limited therapeutic options with low curative potential.^4,5 Thus, there is much interest in methods for the early detection of cancer to achieve better survivorship outcomes.

The objective of early detection is to confirm the presence of cancer or precancerous lesions in an individual at the earliest time to inform management. One approach is screening, where investigations are done proactively for an asymptomatic population to identify individuals with high-risk cancers for further evaluation, such as biopsy or prophylactic therapy.⁶ Organised cancer screening programmes at the state or national levels are often age-based, where all asymptomatic individuals are recommended for an investigation for a particular cancer at a specific frequency once they reach a certain age.⁷ However, recent studies have found that cancer incidence is rising among younger age groups,^8-9 which precludes this increasingly at-risk population from current early detection strategies. Furthermore, age-based screening is agnostic to inter-individual risk profiles, which potentially reduce its diagnostic accuracy¹⁰ and increase screening harms associated with false positive results or overdiagnosis.^11,12 Investigations with higher specificity or sensitivity are often associated with higher cost or invasiveness, such as colonoscopy for colorectal cancer and magnetic resonance imaging (MRI) for prostate cancer, which complicates population-wide adoption. Yet, lower-cost and non-invasive modalities, which may be easily implemented at a population level, are associated with lower sensitivity and/or specificity, such as urine prostate-specific antigen, which can lead to false positives and negatives.

One emerging solution is risk-based screening (RBS), where a detailed cancer risk profile of an individual is used to tailor screening recommendations, such as age of screening, screening modalities and frequency. Risk profiles can include indices, such as family history of malignancy, cancer-related biomarker levels, lifestyle, past medical history and socioeconomic status.^13,14 Recent advances in genomic medicine have also incorporated polygenic risk scores (PRS) or single-nucleotide polymorphisms into these risk profiles. One example is the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), which predicts the chances of a woman carrying breast or ovarian cancer susceptibility genes (e.g. BRCA1, BRCA2) and risk of developing such malignancies.¹⁵ The algorithm computes these probabilities by considering the family history of related cancers, the presence of high-risk gene variants, and associated lifestyle factors such as contraceptive use and mammographic density.¹⁵

Studies have shown that the implementation of BOADICEA and similar breast cancer risk models for RBS is cost-effective¹⁶ and acceptable¹⁷ among females. Although many in silico studies have been published on cancer risk prediction models, the evidence on the practical implementation of RBS remains limited. There have been RBS trials exploring the implementation of risk-based cancer screening, such as the Colorectal cancer RISk Prediction¹⁸ trial in Australia and the Stockholm Model 3 – Magnetic Resonance Imaging trial¹⁹ in Sweden for prostate cancer. Yet to date, no systematic review has been conducted to evaluate the effectiveness of RBS programmes beyond those for breast cancer²⁰ and lung cancer.²¹ As such, the efficacy of RBS across different cancers and the range of methodologies employed have not been summarised. Thus, a systematic review was conducted to (1) summarise current RBS methodologies for each cancer among pragmatic trials; (2) evaluate the effectiveness in terms of accuracy, cost and patient acceptability of implemented RBS programmes; and (3) highlight potential equity gaps in such programmes.

METHODS

The systematic review was conducted with reference to the Cochrane Handbook for Systematic Reviews of Intervention²² and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).²³ The review was prospectively registered in the International Prospective Register of Systematic Reviews (CRD42024542831).

Search strategy

A systematic search was conducted on Embase and MEDLINE on the Ovid platform, PubMed, Scopus, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL) and CINAHL from their respective dates of inception to 8 July 2024. The search strategy comprised controlled search terms, such as “early detection of cancer”, “neoplasms” and “diagnostic screening programs.” Text terms relating to risk stratification, screening programmes and cancer were also incorporated. The strategy was piloted on PubMed, and further reviewed and refined by a medical information specialist. The strategy was then translated to other databases as befitting their native search syntax. The full search strategies can be found in Supplementary Table S1. A bibliometric search of the references of included studies was conducted for completeness.

Study selection and data extraction

Studies investigating the uptake and effectiveness of implemented RBS programmes among asymptomatic participants without a current diagnosis of the cancer being screened were included. The exclusion criteria included studies of paediatric patients, studies of in silico modelling of RBS outcomes, reviews of any kind, conference abstracts, letters and editorials. Title-abstracts retrieved with the aforementioned search strategies were uploaded to Covidence, a collaborative systematic review management platform. Two investigators (YYT and MFBF) independently screened the title-abstracts against the inclusion and exclusion criteria. Full-text papers were then retrieved and independently screened for inclusion by the investigators.

Data extraction was performed with data entered into a collaborative spreadsheet that was piloted on the first 3 studies. The extraction sheet was further refined after discussions among the investigators and deployed for the rest of the articles. Similar to study selection, data extraction was performed independently by the 2 investigators for each article (YYT and MFBF). Primary endpoints were the uptake of the initial risk stratification test and subsequent risk-informed procedures, and the diagnostic accuracy of RBS. Secondary endpoints included the participant acceptability of RBS, cost-effectiveness metrics and long-term mortality and morbidity outcomes.

Any disagreements at the study selection, data extraction and quality assessment stages were resolved via discussions between the investigators (YYT and MFBF). A third review author (ST) was consulted if no consensus was reached.

Quality assessment

The risk of bias of included studies was assessed independently by 2 investigators for each study (YYT and MFBF). Specifically, the Cochrane Risk-of-Bias 2 (RoB2) tool²⁴ was used to assess randomised controlled trials (RCTs), while the Cochrane Risk Of Bias In Non-randomised Studies of Intervention (ROBINS-I) tool²⁵ was used for prospective and retrospective cohort studies. Risk of bias was then visualised using the Risk-of-Bias VISualisation tool²⁶ as traffic-light plots and summary plots.

Data synthesis

Due to the heterogeneous methods and outcomes reported as expected of implementation studies, a quantitative meta-analysis was not conducted. Instead, the outcomes were summarised with descriptive statistics, such as median, interquartile range (IQR) and mean proportions where appropriate. Narrative synthesis was conducted to summarise qualitative aspects of the study characteristics, risk stratification methodologies, follow-up interventions and evaluated outcomes.

RESULTS

The systematic database search for primary studies yielded 6412 citations, of which 770 were duplicates. Among the 5503 citations excluded, primary reasons for exclusion include the absence of implementation of real-world RBS programmes, RBS programmes that did not focus on cancer and inappropriate study designs. The full-texts of 139 citations were retrieved following the title-abstract sieve, of which 106 were excluded for reasons such as lacking real-world implementation of risk stratification or not reporting any outcomes. On searching the bibliography of the included articles, the full-text papers of 12 additional citations were retrieved, of which all were excluded from the review (Fig. 1).

Fig. 1. PRISMA flowchart of study selection.

Hence, 33 studies satisfied the inclusion criteria, and their data were extracted for evidence synthesis,^18,19,27-57 and their characteristics are summarised in Table 1. Of the 33 studies, 21 studies were prospective cohort studies (63.6%),^{19,27,28,30-32,34-37,40,43,45,47,50-52,54-57} 8 were RCTs (24.2%),^{18,33,38,39,41,46,49,53} 3 were retrospective studies of previous or ongoing RBS programmes (9.1%),^29,42,44 and 1 was a non-RCT (3.0%).⁴⁸ The studies were published within a year range of 2008–2024. Most studies (n=22, 66.7%) were multicentre trials at a national level embedded within primary to tertiary care settings,^{18,19,27-29,31,34,36,41-44,46,48-51,53-56} while the remainder were single-centre screening trials (n=11, 33.3%).^{30,32,35,37-40,45,47,52,57} The sample size ranged from 102 participants in a single-centre trial⁵⁰ to 1,429,890 participants in a nationwide cancer screening trial.²⁹

Table 1. Summary of study characteristics.

The most common cancer to be evaluated for RBS was colorectal (n=9, 27.3%),^{18,33,38,43,45-47,51,53} followed by breast (n=7, 21.2%),^{29,31,32,35,36,40,48} then prostate (n=6, 18.2%).^{19,37,41,42,52,56} By region, most studies were conducted in Europe (n=16, 48.5%), followed by the Asia-Pacific (n=12, 36.4%) then North America (n=5, 15.2%). By country, most studies were conducted in China (n=7, 21.2%),^{27,30,45,51-54} followed by the Netherlands (n=4, 12.1%),^28,37,44,46 Sweden,^19,41,56 Australia^18,33,50 and the US^36,42,47 (both n=3, 9.1%, respectively) (Fig. 2). Of the studies with a comparator arm, 9 compared against standard care protocols,^{18,33,35,38,44,48,49,53,55} 3 studies compared against a universal screening protocol,^29,41,46 2 studies compared against no screening^28,39 and 1 study compared against the population with average cancer risk.³⁶

Fig. 2. Distribution of completed RBS programmes worldwide. RBS: risk-based screening

Risk-of-bias outcomes are presented in Figs. 3A–D. Among the RCTs, 4 were rated as low risk of bias,^18,46,49,53 1 with some concerns³⁹ and 3 with high risk of bias.^33,38,41 The domains with significant methodological issues were mainly that of outcome measurement, due to the implementation of participant self-report of screening as the main measurement method. Among the non-randomised studies of intervention, 5 were rated as low risk of bias,^{31,32,40,44,52} 12 had some concerns^{19,29,30,34,43,45,47,48,50,51,54,57} and 8 were rated as high risk of bias.^{27,28,35-37,42,55,56} Significant methodological issues were raised with regard to deviations from the intended intervention due to the lack of compliance reporting and measures to ensure compliance. There were also issues with confounding due to the insufficient reporting of baseline characteristics and absence of confounder adjustment, as well as the selection of outcomes due to the absence of a protocol existing prior to the study publication.

Figs. 3. Traffic-light plots describing the risk of bias as assessed by (A,C) Cochrane Risk-of-Bias 2 tool and (B, D) Cochrane Risk Of Bias In Non-randomised Studies of Interventions stratified by studies and risk-of-bias domains, respectively.

(A)(B)

(C)

(D) 

RBS methods

A summary of risk stratification methods by cancer type is presented in Table 2. Across the 33 studies, 23 utilised some form of imaging or clinical investigation that was specific to the cancer evaluated. These tests include mammogram for breast cancer, prostate serum antigen test for prostate cancer, fecal immunochemistry test for colorectal cancer and high-risk human papillomavirus types testing for cervical cancer. One study conducted Epstein-Barr virus serology testing for the risk stratification of nasopharyngeal carcinoma.⁵⁴ Twenty-three studies assessed the level of genetic risk of the participant, mostly via family history of cancer, while 4 studies conducted genetic testing on recruited participants to assess for high-risk cancer genetic polymorphisms to calculate a polygenic risk score.^19,31,40,41 Otherwise, cancer risk score was calculated with previously validated risk models incorporating participant characteristics, relevant family and personal history and symptoms, such as the Gail model³² and Tyrer-Cuzick model⁴⁸ for breast cancer. Clinical questionnaires were deployed in 24 studies for risk assessment, of which 20 studies^{18,29,32-35,37,38,41-43,45-48,50,51,53,54,57} assessed the family history of cancer or related pathologies, such as polyps in colorectal cancer.⁴⁵ Eleven studies assessed lifestyle factors that were associated with the cancer risk evaluated in the questionnaire,^{18,31,32,34,38,39,46,49,51,53,57} the most common of which was smoking history. Thirteen studies assessed the previous medical history that was associated with the cancer risk evaluated,^{18,19,31,32,34,38,39,41,43,47,49,51,57} such as a previous diagnosis of inflammatory bowel disease in colorectal cancer⁴³ or a prescription of contraceptives in breast cancer.^31,32 Seven studies assessed self-reported cancer-specific symptomatology among the participants.^{18,37,38,43,45,49,57}

Table 2. Summary of risk stratification methods reported across included studies.

After collecting information on risk factors, stratification was done primarily via 3 approaches. Most studies stratified interventions by the presence or absence of a singular or combination of risk factors through an algorithmic approach (n=16, 48.5%),^{27-30,32,35,36,39,41,44,45,49,52,53,56} while 13 studies calculated a risk score using a previously validated model to stratify participants.^{18,19,31,34,37,38,40,46-48,51,54,57} Validated models include the Stockholm-3 model for prostate cancer¹⁹ and the PLCO_m2012 model for lung cancer.³⁴ The remaining 3 studies involved a risk assessment by the physician to personalise a risk-stratified intervention for the participant.^42,43,50 Across the studies, participants would be stratified between 2 and 3 risk strata, each with a set of strata-specific interventions. One study further personalised these interventions to the individual risk profile of the participants in addition to strata-specific interventions, specifically personalising the initiation age of mammography and MRI of the breast.⁴⁰

A summary of risk-stratified interventions by cancer type is presented in Table 3. Participants within the high-risk strata were often recommended invasive procedures or biopsies, such as colonoscopy in colorectal cancer screening^{33,38,43,45,46,51,53} and referral to a specialist or an oncology clinic for follow-up.^{18,19,28,33,42,56} One study further recommended discussion with a clinician for the initiation of chemoprevention therapy of breast cancer.⁴⁰ Participants within the moderate-risk strata were recommended non-invasive tests instead or returned to routine screening with a higher frequency than average participants.

Table 3. Summary of follow-up interventions for each cancer type stratified by risk level.

RBS outcomes

Cancer risk and survivorship outcomes

Of the 33 studies, 10 studies did not record cancer diagnoses as an outcome measure among the risk-stratified participants.^{18,31,33,38,40,41,43,44,48,50} Seven studies found that higher risk-strata participants had a statistically significant higher rate of cancer diagnosis than lower risk-strata participants,^{28,30,39,42,44,50,54} which concurred with the theoretical risk model findings of the respective studies. In the remaining studies that reported cancer diagnosis endpoints, 4 studies reported a follow-up duration of less than a year,^35,37,46,47 14 studies reported a follow-up duration between 1 and 5 years,^{27,30,32,36,42,45,49,52,53,55-57,70,72} while 5 studies followed up with patients for 5 years or more.^{28,29,39,51,54} In terms of outcomes, 2 studies found that RBS participants had a statistically significant higher rate of cancer diagnosis than control participants,^36,41 while 3 studies found that RBS was non-inferior to the control paradigm in diagnosing cancer.^29,46,53 Only one study, the Danish Lung Cancer Screening Trial, reported on the mortality outcomes of participants, specifically that there was no significant differences in lung cancer mortality between the participants that underwent RBS and those that did not undergo screening.³⁹

Only 12 studies reported at least one measure of diagnostic test accuracy of the implemented RBS programme,^{28,30,34,36,40,44-46,54,55,57} such as sensitivity or area under the receiver operating characteristic curve.

Participant uptake and acceptability

Nine studies reported on the extent of uptake of strata-specific interventions.^{18,19,29,30,33,34,37,38,43,44,46-49,51,53,56,57} The median proportion of high-risk participants that received their strata-specific intervention was 71.3% (IQR 38.8%), 75.4% (IQR 38.3%) for moderate-risk participants and 67.9% (IQR 55.0%) for low-risk participants. One study found that risk-stratified participants who were made aware of their cancer risk assessment were significantly more likely to undergo risk-appropriate screening than those who did not.¹⁸ Three studies reported significant positive changes in patient-reported outcomes, such as decreased anxiety towards cancer, high satisfaction with the screening process or increased perceived risk of cancer.^18,34,50 One study further reported qualitative findings, following an in-depth interview of the participants, which concluded that participants found genetic counselling useful as they gained knowledge of their own risk factors for cancer and were empowered to proactively self-monitor or act upon their cancer risk profile.⁵⁰

Cost-effectiveness and healthcare utilisation

Seven studies analysed the comprehensive health services and outcomes of RBS programmes, yielding promising results.^{18,19,32,34,49,51,53} The majority of these studies^{18,32,49,51,53} concluded that RBS can lead to potential cost savings and a significant increase in quality-adjusted life years compared to existing screening guidelines. Additionally, one study found that RBS resulted in substantially reduced rates of unnecessary biopsies,¹⁹ while another study revealed that RBS programmes did not lead to increased waiting times for computed tomography scans, despite the increased scan volume.³⁴

DISCUSSION

Significant developments have facilitated the translation of cancer risk prediction models into the real-world implementation of RBS programmes to stratify asymptomatic individuals for risk-appropriate screening. To the authors’ knowledge, this is the first systematic review to consolidate the evidence base for the real-world implementation of RBS programmes. A majority of the studies explored screening for colorectal cancer, followed by breast and prostate cancer with most RBS programmes employing algorithm-driven risk stratification or validated risk scoring equation based on the presence of risk factors. Although few studies have recorded cancer diagnoses among participants, available data indicate RBS programmes either outperform or demonstrate non-inferiority to standard screening guidelines. Furthermore, studies assessing participant acceptability found that those enrolled in RBS viewed such programmes positively, citing improvements in education towards cancer risk and their options with respect to their individual propensities for cancer.

Although many risk models for various cancer types have been elucidated, the implementation of such models to inform risk-appropriate screening in the real-world setting remains poorly studied. Various in silico studies have demonstrated the potential cost-effectiveness of RBS over age-based screening paradigms,^58-60 yet such cost-savings may be erroneously high as modelling studies often overestimate the real-world compliance rate to risk-appropriate screening among the participants. Hence, future studies on cancer screening can consider reporting health services outcomes, such as cost-savings incurred or disability-adjusted life-years, so as to quantify the cost-effectiveness of RBS in relation to the upfront costs of risk stratification. Factors impacting the attendance of RBS and subsequent follow-up visits are similar to that of traditional screening,⁶¹ including perceived lack of self-efficacy, fear of cancer diagnosis, cultural beliefs towards cancer and inconvenience.^17,62,63 Recent work has shown that one way to overcome these barriers is through timely and reassuring communication of results and their implications to patients, as well as centring the discussion of cancer risk management around autonomy and self-efficacy.⁶² Our review found that participants in the higher risk strata had higher adherence to follow-up, which implies that differing sets of facilitators and barriers to RBS and follow-up exist between participants of different risk-strata. Thus, future research should focus on understanding these stratum-specific barriers to RBS attendance and follow-up adherence, thus enabling the development of targeted interventions that can be implemented alongside RBS programmes. Such studies can be part of a broader implementation framework, which can include approaches such as but not limited to (1) stratum-specific barrier assessment studies, (2) development of targeted interventions and (3) research into comparative effectiveness across different implementation strategies.

There may be public and provider resistance against the de-implementation of screening among supposedly low-risk participants if RBS were to be effectuated,⁶⁴ as it contradicts pre-existing age-based screening guidelines as recognised in the public consciousness.^65,66 RBS may expose high-risk individuals to discrimination by insurers and employers. Furthermore, RBS that implements PRS derived from genomic testing may face even more significant challenges, such as high costs⁶⁷ and the ethico-legal consequences following genomic testing, including data privacy, test result uncertainty and conflict with personal and religious values.^68,69 Thus, healthcare system administrators and policymakers may consider consulting public opinion and work closely with private insurers to design fair and reasonable risk-stratification screening programmes. Subsequently, extensive public communication might be required to address the complexity underlying RBS programmes and to reconcile pre-existing sociocultural beliefs and ideas towards cancer screening, so as to enhance the public enthusiasm and uptake of such programmes. There is a role for healthcare professionals (HCPs) in the promotion of RBS as well, especially general practitioners and family medicine specialists, as they are often the first healthcare encounter that most patients have. A recent review reported that HCPs are more likely to accept and promote RBS if presented with robust evidence of its efficacy and cost-effectiveness that outweighs the need for more resources and patient-facing work.⁷⁰ Thus, healthcare administrators and policymakers can also consider providing more support to HCPs on-the-ground in the implementation of such programmes, by having guideline update sessions, providing more administrative support or streamlining care pathways for referrals.  

Even if RBS were to be implemented in spite of the aforementioned barriers, consideration must be given to underserved populations and the applicability of models to non-Caucasian populations. In this systematic review and among other studies, most risk-prediction models were derived from the case-control studies of majority-Caucasian cohorts, such as the Stockholm-3 model,⁷¹ BOADICEA model⁷² and PLCO_m2012⁷³ model. Thus, the transferability of these models to non-Caucasian populations is limited, which explains the observed lack of RBS studies in the Asia-Pacific, South American and Middle Eastern–North African (MENA) regions. Yet, it is precisely these same countries that may benefit the most from RBS due to the potential cost-savings and patient harm reduction observed in successful programmes, suggesting its suitability for adoption in low-resource regions within those geographies. As such, there exist ethnic disparities in early cancer detection tools, which are further compounded by existing socioeconomic inequalities that already complicate healthcare access among underserved populations.^74,75 Of note, China is an exception as researchers were able to utilise the China Kadoorie Biobank to derive risk-prediction models representative of their population,^76-78 although no real-world implementation of these models has been recorded to our knowledge. One study⁵³ also utilised the Asia-Pacific Colorectal Screening Score⁷⁹ in the implementation of RBS, which is more representative of Asian populations.

Despite the above problems, RBS remains a promising way forward for cancer screening based on the findings of this review. First, RBS was able to reduce costs and excessive patient harm by reducing the number of unnecessary investigations while maintaining good accuracy in diagnosing true cancers. This was achieved when RBS programmes were able to match the appropriately powered investigation to the risk level of the individual. Furthermore, the participants viewed genomic testing for cancer screening positively, and the newfound knowledge empowered them to manage their cancer risk levels appropriately. Hence, such factors underlying the acceptability or refusal of an individual to RBS must be better studied to inform the real-world implementation of RBS, such that it can achieve high uptake in both screening and follow-up across all demographics.

In terms of quality assessment, study quality was poor among the non-randomised studies of intervention, as only 5 studies were rated with a low overall risk of bias. One significant factor was the absence of measures to account for deviations from the risk-stratified interventions among the participants. Studies either reported a low compliance rate of risk-stratified interventions among the participants or did not consider the capacity of participants to seek care and opinions extraneous to the study paradigm. This bias further translated to the high rates of lost-to-follow-up among some of the studies as well, since participants who did not comply with the risk-stratified intervention may drop out from the study altogether. Study quality was higher but could be improved among the RCTs, especially in terms of outcome measurement. This was so as among trials that assessed the initial compliance of RBS, outcomes were measured via participant self-reporting, which is less accurate than medical record linkage. Otherwise, the RCTs were generally well-designed and likely to report unbiased findings. In addition to risk of bias assessed by RoB2 and ROBINS-I, the authors further identified the potential for both differential verification bias and lead-time bias in these studies. Differential verification biases may arise because low-risk participants often received less rigorous or no follow-up investigations compared to high-risk participants, leading to the inconsistent verification of outcomes between groups. This could impact the assessment of diagnostic accuracy by inflating the detection rates among high-risk participants who received more intensive evaluations. Additionally, lead-time bias may influence survival outcomes, as high-risk participants are likely diagnosed earlier due to expedited diagnostic testing, which may appear to extend survival compared to low-risk individuals. Studies evaluating treatment, morbidity and mortality outcomes among these cohorts should therefore account for both differential verification bias and lead-time bias to provide a more accurate interpretation of RBS effectiveness.

The primary strength of our review was the comprehensiveness of the search done across 7 databases. Furthermore, our review focused on implementation trials to address the translation gap of cancer risk prediction models with a comprehensive synthesis of outcomes beyond that of usual clinical indicators, such as diagnostic test accuracy measures or mortality estimates. However, there are some limitations. The main limitation is that of the significant heterogeneity in study designs and outcomes reported across the included studies. As such, meta-analysis was precluded from our review as well as limiting the comparability of results between trials. However, as RBS is a complex public health intervention, such heterogeneity is expected especially in a real-world implementation setting. Thus, the authors attempted to improve the interpretability of results by using a systematic approach in narrative synthesis and summarising key risk stratification methodologies by cancer types.

CONCLUSION

The RBS of cancer is being implemented worldwide, following the in silico development and validation of various cancer risk prediction models. A majority of real-world-implemented RBS programmes screened for colorectal cancer, followed by breast and prostate cancer. Most studies were conducted in either the North American or European region, with most Asian studies conducted in China. More risk prediction models need to be developed primarily from non-Caucasian cohorts to facilitate the translation of RBS to Asian, South American and MENA settings. This review also suggests concerns regarding the uptake of risk-appropriate screening in real-world settings, necessitating qualitative studies to elucidate the facilitators and barriers of RBS among patients and clinicians alike. As RBS becomes increasingly mainstream, subsequent studies must take care in adjusting for potential lead time and verification bias when assessing survivorship outcomes, while also evaluating the cost-effectiveness and ethico-legal considerations of personalised screening strategies.

Supplementary material

Table S1. Complete search strategies used for retrieval of articles in this systematic review in the following databases: (A) CENTRAL, (B) CINAHL, (C) Embase and MEDLINE on OvidSP, (D) PubMed, (E) SCOPUS and (F) Web of Science.

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