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This scoping review aims to systematically gather evidence from personalized cancer-screening studies across various cancers, summarize key components and outcomes, and provide implications for a future personalized melanoma-screening strategy. Peer-reviewed articles and clinical trial databases were searched for, with restrictions on language and publication date. Sixteen distinct studies were identified and included in this review. The studies' results were synthesized according to key components, including risk assessment, risk thresholds, screening pathways, and primary outcomes of interest. Studies most frequently reported about breast cancers (n = 7), followed by colorectal (n = 5), prostate (n = 2), lung (n = 1), and ovarian cancers (n = 1). The identified screening programs were evaluated predominately in Europe (n = 6) and North America (n = 4). The studies employed multiple different risk assessment tools, screening schedules, and outcome measurements, with few consistent approaches identified across the studies. The benefit-harm assessment of each proposed personalized screening program indicated that the majority were feasible and effective. The establishment of a personalized screening program is complex, but results of the reviewed studies indicate that it is feasible, can improve participation rates, and screening outcomes. While the review primarily examines screening programs for cancers other than melanoma, the insights can be used to inform the development of a personalized melanoma screening strategy.

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BACKGROUND: Recommendations regarding personalized lung cancer screening are being informed by natural-history modeling. Therefore, understanding how differences in model assumptions affect model-based personalized screening recommendations is essential. DESIGN: Five Cancer Intervention and Surveillance Modeling Network (CISNET) models were evaluated. Lung cancer incidence, mortality, and stage distributions were compared across 4 theoretical scenarios to assess model assumptions regarding 1) sojourn times, 2) stage-specific sensitivities, and 3) screening-induced lung cancer mortality reductions. Analyses were stratified by sex and smoking behavior. RESULTS: Most cancers had sojourn times <5 y (model range [MR]; lowest to highest value across models: 83.5%-98.7% of cancers). However, cancer aggressiveness still varied across models, as demonstrated by differences in proportions of cancers with sojourn times <2 y (MR: 42.5%-64.6%) and 2 to 4 y (MR: 28.8%-43.6%). Stage-specific sensitivity varied, particularly for stage I (MR: 31.3%-91.5%). Screening reduced stage IV incidence in most models for 1 y postscreening; increased sensitivity prolonged this period to 2 to 5 y. Screening-induced lung cancer mortality reductions among lung cancers detected at screening ranged widely (MR: 14.6%-48.9%), demonstrating variations in modeled treatment effectiveness of screen-detected cases. All models assumed longer sojourn times and greater screening-induced lung cancer mortality reductions for women. Models assuming differences in cancer epidemiology by smoking behaviors assumed shorter sojourn times and lower screening-induced lung cancer mortality reductions for heavy smokers. CONCLUSIONS: Model-based personalized screening recommendations are primarily driven by assumptions regarding sojourn times (favoring longer intervals for groups more likely to develop less aggressive cancers), sensitivity (higher sensitivities favoring longer intervals), and screening-induced mortality reductions (greater reductions favoring shorter intervals). IMPLICATIONS: Models suggest longer screening intervals may be feasible and benefits may be greater for women and light smokers. HIGHLIGHTS: Natural-history models are increasingly used to inform lung cancer screening, but causes for variations between models are difficult to assess.This is the first evaluation of these causes and their impact on personalized screening recommendations through easily interpretable metrics.Models vary regarding sojourn times, stage-specific sensitivities, and screening-induced lung cancer mortality reductions.Model outcomes were similar in predicting greater screening benefits for women and potentially light smokers. Longer screening intervals may be feasible for women and light smokers.

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BACKGROUND: Personalized breast cancer screening is a novel strategy that estimates individual risk based on age, breast density, family history of breast cancer, personal history of benign breast lesions, and polygenic risk. Its goal is to propose personalized early detection recommendations for women in the target population based on their individual risk. Our aim was to synthesize the factors that influence women's decision to participate in personalized breast cancer screening, from the perspective of women and health care professionals. METHODS: Systematic review of qualitative evidence on factors influencing participation in personalized Breast Cancer Screening. We searched in Medline, Web of science, Scopus, EMBASE, CINAHL and PsycINFO for qualitative and mixed methods studies published up to March 2022. Two reviewers conducted study selection and extracted main findings. We applied the best-fit framework synthesis and adopted the Multilevel influences on the cancer care continuum model for analysis. After organizing initial codes into the seven levels of the selected model, we followed thematic analysis and developed descriptive and analytical themes. We assessed the methodological quality with the Critical Appraisal Skills Program tool. RESULTS: We identified 18 studies published between 2017 and 2022, conducted in developed countries. Nine studies were focused on women (n = 478) and in four studies women had participated in a personalized screening program. Nine studies focused in health care professionals (n = 162) and were conducted in primary care and breast cancer screening program settings. Factors influencing women's decision to participate relate to the women themselves, the type of program (personalized breast cancer screening) and perspective of health care professionals. Factors that determined women participation included persistent beliefs and insufficient knowledge about breast cancer and personalized screening, variable psychological reactions, and negative attitudes towards breast cancer risk estimates. Other factors against participation were insufficient health care professionals knowledge on genetics related to breast cancer and personalized screening process. The factors that were favourable included the women's perceived benefits for themselves and the positive impact on health systems. CONCLUSION: We identified the main factors influencing women's decisions to participate in personalized breast cancer screening. Factors related to women, were the most relevant negative factors. A future implementation requires improving health literacy for women and health care professionals, as well as raising awareness of the strategy in society.

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AIM: In the Danish Colorectal Cancer Screening Program (DCCSP), 37% of participants undergoing colonoscopy have a negative result with no obvious findings that can be attributed to a positive faecal immunochemical test (FIT). The aim of this work was to identify predictors for a negative colonoscopy in DCCSP participants with a positive FIT. METHOD: We included 73 655 FIT-positive DCCSP participants using the Danish Colorectal Cancer Screening Database and linked their screening results with data from several other national health registers. We stratified participants by all predictors, and compared them using multivariate logistic regression analysis. Results are reported as odds ratios (ORs). RESULTS: We found that having a condition linked to gastrointestinal bleeding, for example fissures, haemorrhoids and inflammatory bowel disease, was strongly associated with the probability of having a negative colonoscopy [OR 2.77 (95% CI 2.59, 2.96)]. FIT concentration was inversely related to the probability of a negative colonoscopy, the OR decreased steadily from 0.79 (95% CI 0.75, 0.83) in the 40-59 µg/g group, to 0.44 (95% CI 0.42, 0.46) in the ≥200 µg/g group. Women had a 1.64 (95% CI 1.59, 1.70) times higher probability of a negative colonoscopy than men. CONCLUSION: Our findings indicate that baseline conditions linked to gastrointestinal bleeding are an associating factor with having a negative colonoscopy. The same is true for low FIT concentration and female sex. Further studies with similar findings could suggest that an incorporation of these factors into a personalized screening approach by differentiating between diagnostic modalities could improve the process for the participant while alleviating the health care system.

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BACKGROUND: The current one-size-fits-all screening strategy for lung cancer is not suitable for personalized screening. RESEARCH QUESTION: What is the risk-adapted starting age of lung cancer screening with comprehensive consideration of risk factors? STUDY DESIGN AND METHODS: The National Lung Cancer Screening program, a multicenter, population-based, prospective cohort study, was analyzed. Information on risk factor exposure was collected during the baseline risk assessment. A Cox proportional hazards model was used to estimate the association between risk factors and lung cancer incidence. Age-specific 10-year cumulative risk was calculated to determine the age at which individuals with various risk factors reached the equivalent risk level as individuals aged ≥ 50 years with active tobacco use and a ≥ 20 pack-year smoking history. RESULTS: Of the 1,031,911 participants enrolled in this study, 3,908 demonstrated lung cancer after a median follow-up of 3.8 years. We identified seven risk factors for lung cancer, including pack-years of smoking, secondhand smoke exposure, family history of lung cancer in first-degree relatives, history of respiratory diseases, occupational hazardous exposure, BMI, and diabetes. The 10-year cumulative risk of lung cancer for people aged ≥ 50 years with active tobacco use and a ≥ 20 pack-year smoking history was 1.37%, which was treated as the risk threshold for screening. Individuals who never smoked and those with active tobacco use and a < 30-pack-year history of smoking reached the equivalent risk level 1 to 14 years later compared with the starting age of 50 years. Men with active tobacco use, a ≥ 30-pack-year history of smoking, and concurrent respiratory diseases or diabetes should be screened 1 year earlier at the age of 49 years. INTERPRETATION: The personalized risk-adapted starting ages for lung cancer screening, based on the principle of equal management of equal risk, can served as an optimized screening strategy to identify high-risk individuals.

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BACKGROUND: Incidence of and mortality from colorectal cancer (CRC) can be effectively reduced by screening with the fecal immunochemical test (FIT) or colonoscopy. Individual risk to develop CRC within 15 years varies from <1% to >15% among people aged 50 to 75 years. Communicating personalized CRC risk and appropriate screening recommendations could improve the risk-benefit balance of screening test allocations and optimize the use of limited colonoscopy resources. However, significant uncertainty exists regarding the feasibility and efficacy of risk-based screening. OBJECTIVE: We aim to study the effect of communicating individual CRC risk and a risk-based recommendation of the FIT or colonoscopy on participants' choice of screening test. We will also assess the feasibility of a larger clinical trial designed to evaluate the impact of personalized screening on clinical outcomes. METHODS: We will perform a pilot randomized controlled trial among 880 residents aged 50 to 69 years eligible to participate in the organized screening program of the Vaud canton, Switzerland. Participants will be recruited by mail by the Vaud CRC screening program. Primary and secondary outcomes will be self-assessed through questionnaires. The risk score will be calculated using the open-source QCancer calculator that was validated in the United Kingdom. Participants will be stratified into 3 groups-low (<3%), moderate (3% to <6%), and high (≥6%) risk-according to their 15-year CRC risk and randomized within each risk stratum. The intervention group participants will receive a newly designed brochure with their personalized risk and screening recommendations. The control group will receive the usual brochure of the Vaud CRC screening program. Our primary outcome, measured using a self-administered questionnaire, is appropriate screening uptake 6 months after the intervention. Screening will be defined as appropriate if participants at high risk undertake colonoscopy and participants at low risk undertake the FIT. We will also measure the acceptability of the risk score and screening recommendations and the psychological factors influencing screening behavior. We will also assess the feasibility of a full-scale randomized controlled trial. RESULTS: We expect that a total sample of 880 individuals will allow us to detect a difference of 10% (α=5%) between groups. The main outcome will be analyzed using a 2-tailed chi-squared test. We expect that appropriate screening uptake will be higher in the intervention group. No difference in overall screening uptake is expected. CONCLUSIONS: We will test the impact of personalized risk information and screening recommendations on participants' choice of screening test in an organized screening program. This study should advance our understanding of the feasibility of large-scale risk-based CRC screening. Our results may provide insights into the optimization of CRC screening by offering screening options with a better risk-benefit balance and optimizing the use of resources. TRIAL REGISTRATION: ClinicalTrials.gov NCT05357508; https://www.clinicaltrials.gov/study/NCT05357508. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46865.

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Lung cancer has one of the worst morbidity and fatality rates of any malignant tumour. Most lung cancers are discovered in the middle and late stages of the disease, when treatment choices are limited, and patients' survival rate is low. The aim of lung cancer screening is the identification of lung malignancies in the early stage of the disease, when more options for effective treatments are available, to improve the patients' outcomes. The desire to improve the efficacy and efficiency of clinical care continues to drive multiple innovations into practice for better patient management, and in this context, artificial intelligence (AI) plays a key role. AI may have a role in each process of the lung cancer screening workflow. First, in the acquisition of low-dose computed tomography for screening programs, AI-based reconstruction allows a further dose reduction, while still maintaining an optimal image quality. AI can help the personalization of screening programs through risk stratification based on the collection and analysis of a huge amount of imaging and clinical data. A computer-aided detection (CAD) system provides automatic detection of potential lung nodules with high sensitivity, working as a concurrent or second reader and reducing the time needed for image interpretation. Once a nodule has been detected, it should be characterized as benign or malignant. Two AI-based approaches are available to perform this task: the first one is represented by automatic segmentation with a consequent assessment of the lesion size, volume, and densitometric features; the second consists of segmentation first, followed by radiomic features extraction to characterize the whole abnormalities providing the so-called "virtual biopsy". This narrative review aims to provide an overview of all possible AI applications in lung cancer screening.

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Given the controversy over the effectiveness of age-based breast cancer (BC) screening, offering risk-stratified screening to women may be a way to improve patient outcomes with detection of earlier-stage disease. While this approach seems promising, its integration requires the buy-in of many stakeholders. In this cross-sectional study, we surveyed Canadian healthcare professionals about their views and attitudes toward a risk-stratified BC screening approach. An anonymous online questionnaire was disseminated through Canadian healthcare professional associations between November 2020 and May 2021. Information collected included attitudes toward BC screening recommendations based on individual risk, comfort and perceived readiness related to the possible implementation of this approach. Close to 90% of the 593 respondents agreed with increased frequency and earlier initiation of BC screening for women at high risk. However, only 9% agreed with the idea of not offering BC screening to women at very low risk. Respondents indicated that primary care physicians and nurse practitioners should play a leading role in the risk-stratified BC screening approach. This survey identifies health services and policy enhancements that would be needed to support future implementation of a risk-stratified BC screening approach in healthcare systems in Canada and other countries.

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Purpose: Breast cancer screening is predominantly performed using digital mammography (DM), but digital breast tomosynthesis (DBT) has higher sensitivity. DBT demands more resources than DM, and it might be more feasible to reserve DBT for women with a clear benefit from the technique. We explore if artificial intelligence (AI) can select women who would benefit from DBT imaging. Approach: We used data from Malmö Breast Tomosynthesis Screening Trial, where all women prospectively were examined with separately double read DM and DBT. We retrospectively analyzed DM examinations (n=14768) with a breast cancer detection system and used the provided risk score (1 to 10) for risk stratification. We tested how different score thresholds for adding DBT to an initial DM affects the number of detected cancers, additional DBT examinations needed, detection rate, and false positives. Results: If using a threshold of 9.0, 25 (26%) more cancers would be detected compared to using DM alone. Of the 41 cancers only detected on DBT, 61% would be detected, with only 1797 (12%) of the women examined with both DM and DBT. The detection rate for the added DBT would be 14/1000 women, whereas the false-positive recalls would be increased with 58 (21%). Conclusion: Using DBT only for selected high gain cases could be an alternative to complete DBT screening. AI can analyze initial DM images to identify high gain cases where DBT can be added during the same visit. There might be logistical challenges, and further studies in a prospective setting are necessary.

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PURPOSE: The European Society on Breast Imaging has recommended supplemental magnetic resonance imaging (MRI) every two to four years for women with mammographically dense breasts. This may not be feasible in many screening programs. Also, the European Commission Initiative on Breast Cancer suggests not implementing screening with MRI. By analyzing interval cancers and time from screening to diagnosis by density, we present alternative screening strategies for women with dense breasts. METHODS: Our BreastScreen Norway cohort included 508 536 screening examinations, including 3125 screen-detected and 945 interval breast cancers. Time from screening to interval cancer was stratified by density measured by an automated software and classified into Volpara Density Grades (VDGs) 1-4. Examinations with volumetric density ≤3.4% were categorized as VDG1, 3.5%-7.4% as VDG2, 7.5%-15.4% as VDG3, and ≥15.5% as VDG4. Interval cancer rates were also determined by continuous density measures. RESULTS: Median time from screening to interval cancer was 496 (IQR: 391-587) days for VDG1, 500 (IQR: 350-616) for VDG2, 482 (IQR: 309-595) for VDG3 and 427 (IQR: 266-577) for VDG4. A total of 35.9% of the interval cancers among VDG4 were detected within the first year of the biennial screening interval. For VDG2, 26.3% were detected within the first year. The highest annual interval cancer rate (2.7 per 1000 examinations) was observed for VDG4 in the second year of the biennial interval. CONCLUSIONS: Annual screening of women with extremely dense breasts may reduce the interval cancer rate and increase program-wide sensitivity, especially in settings where supplemental MRI screening is not feasible.

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BACKGROUND & AIMS: A one-size-fits-all approach to colorectal cancer (CRC) screening that does not account for CRC risk factors is not conducive to personalized screening. On the basis of the principle of equal management of equal risks, we aimed to tailor and validate risk-adapted starting ages of CRC screening for individuals with different CRC risk factors. METHODS: A multi-center community-based population cohort (N = 3,165,088) was used to evaluate the starting age of CRC screening with comprehensive consideration of risk factors. Age-specific 10-year cumulative risk curves were used to determine when individuals at greater risk for CRC reached the same risk level as the 50-year-old general population, which is currently the recommended starting age for CRC screening in China. RESULTS: During the study follow-up period (2013-2021), 4,840 incident CRCs were recorded. Family history of CRC, adverse lifestyle, and comorbidities demonstrated heterogeneous associations with CRC risk (hazard ratios, 1.05-1.55; P < .05). Men and women with CRC family history and at least 2 risk factors reached the standard benchmark risk (0.28%) for screening at the age of 40, 10 years earlier than their peers without risk factors in the general population. Proposed starting ages for CRC screening were validated in an independent community-based population cohort (N = 1,023,367). CONCLUSIONS: We determined a risk-adapted CRC screening starting age for individuals with various CRC risk factors. Earlier, personalized screening based on these findings could allow for scarce health resources to be dedicated to individuals who benefit most.

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BACKGROUND & AIMS: The screening yield and related cost of a risk-adapted screening approach compared with established screening strategies in population-based colorectal cancer (CRC) screening are not clear. METHODS: We randomly allocated 19,373 participants into 1 of the 3 screening arms in a 1:2:2 ratio: (1) one-time colonoscopy (n = 3883); (2) annual fecal immunochemical test (FIT) (n = 7793); (3) annual risk-adapted screening (n = 7697), in which, based on the risk-stratification score, high-risk participants were referred for colonoscopy and low-risk ones were referred for FIT. Three consecutive screening rounds were conducted for both the FIT and the risk-adapted screening arms. Follow-up to trace the health outcome for all the participants was conducted over the 3-year study period. The detection rate of advanced colorectal neoplasia (CRC and advanced precancerous lesions) was the main outcome. The trial was registered in the Chinese Clinical Trial Registry (number: ChiCTR1800015506). RESULTS: In the colonoscopy, FIT, and risk-adapted screening arms over 3 screening rounds, the participation rates were 42.4%, 99.3%, and 89.2%, respectively; the detection rates for advanced neoplasm (intention-to-treat analysis) were 2.76%, 2.17%, and 2.35%, respectively, with an odds ratio (OR)colonoscopy vs FIT of 1.27 (95% confidence interval [CI]: 0.99-1.63; P = .056), an ORcolonoscopy vsrisk-adapted screening of 1.17 (95% CI, 0.91-1.49; P = .218), and an ORrisk-adapted screeningvs FIT of 1.09 (95% CI, 0.88-1.35; P = .438); the numbers of colonoscopies needed to detect 1 advanced neoplasm were 15.4, 7.8, and 10.2, respectively; the costs for detecting 1 advanced neoplasm from a government perspective using package payment format were 6928 Chinese Yuan (CNY) ($1004), 5821 CNY ($844), and 6694 CNY ($970), respectively. CONCLUSIONS: The risk-adapted approach is a feasible and cost-favorable strategy for population-based CRC screening and therefore could complement the well-established one-time colonoscopy and annual repeated FIT screening strategies. (Chinese Clinical Trial Registry; ChiCTR1800015506).

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The aim of this study was to assess the acceptability and feasibility of offering risk-based breast cancer screening and its integration into regular clinical practice. A single-arm proof-of-concept trial was conducted with a sample of 387 women aged 40-50 years residing in the city of Lleida (Spain). The study intervention consisted of breast cancer risk estimation, risk communication and screening recommendations, and a follow-up. A polygenic risk score with 83 single nucleotide polymorphisms was used to update the Breast Cancer Surveillance Consortium risk model and estimate the 5-year absolute risk of breast cancer. The women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, more frequently inviting women at higher-than-average risk. A lower intensity screening for women at lower risk was not as welcome, although half of the participants would accept it. Knowledge of the benefits and harms of breast screening was low, especially with regard to false positives and overdiagnosis. The women expressed a high understanding of individual risk and screening recommendations. The participants' intention to participate in risk-based screening and satisfaction at 1-year were very high.

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French breast cancer screening is based on organized screening with a mammography every two years for women between 50 and 74, and individualized screening for women at high or very high risk of breast cancer (personal history of breast cancer or atypical breast lesion or thoracic radiotherapy before the age of 25, high family risk without genetic mutation, genetic mutation). A novel approach of risk-based breast cancer screening is currently under evaluation in many countries, including France. This personalized screening, based on individual risk of having breast cancer in the next years, uses algorithms which combine clinical parameters, mammographic density, familial history and genomic (using polygenic risk score), to estimate breast cancer risk and adapt screening's frequency.

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PURPOSE: The purpose is to accurately identify women at high risk of developing cervical cancer so as to optimize cervical screening strategies and make better use of medical resources. However, the predictive models currently in use require clinical physiological and biochemical indicators, resulting in a smaller scope of application. Stacking-integrated machine learning (SIML) is an advanced machine learning technique that combined multiple learning algorithms to improve predictive performance. This study aimed to develop a stacking-integrated model that can be used to identify women at high risk of developing cervical cancer based on their demographic, behavioral, and historical clinical factors. METHODS: The data of 858 women screened for cervical cancer at a Venezuelan Hospital were used to develop the SIML algorithm. The screening data were randomly split into training data (80%) that were used to develop the algorithm and testing data (20%) that were used to validate the accuracy of the algorithms. The random forest (RF) model and univariate logistic regression were used to identify predictive features for developing cervical cancer. Twelve well-known ML algorithms were selected, and their performances in predicting cervical cancer were compared. A correlation coefficient matrix was used to cluster the models based on their performance. The SIML was then developed using the best-performing techniques. The sensitivity, specificity, and area under the curve (AUC) of all models were calculated. RESULTS: The RF model identified 18 features predictive of developing cervical cancer. The use of hormonal contraceptives was considered as the most important risk factor, followed by the number of pregnancies, years of smoking, and the number of sexual partners. The SIML algorithm had the best overall performance when compared with other methods and reached an AUC, sensitivity, and specificity of 0.877, 81.8%, and 81.9%, respectively. CONCLUSION: This study shows that SIML can be used to accurately identify women at high risk of developing cervical cancer. This model could be used to personalize the screening program by optimizing the screening interval and care plan in high- and low-risk patients based on their demographics, behavioral patterns, and clinical data.

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This study explored the barriers and facilitators to the implementation of a risk-based breast cancer screening program from the point of view of Spanish health professionals. A cross-sectional study with 220 Spanish health professionals was designed. Data were collected in 2020 via a web-based survey and included the advantages and disadvantages of risk-based screening and barriers and facilitators for the implementation of the program. Descriptive statistics and Likert scale responses analyzed as category-ordered data were obtained. The risk-based screening was considered important or very important to reduce breast cancer mortality and promote a more proactive role for women in breast cancer prevention, to increase coverage for women under 50 years, to promote a breast cancer prevention strategy for women at high risk, and to increase efficiency and effectiveness. Switching to a risk-based program from an age-based program was rated as important or very important by 85% of participants. As barriers for implementation, risk communication, the workload of health professionals, and limited human and financial resources were mentioned. Despite the barriers, there is good acceptance, and it seems feasible, from the perspective of health professionals, to implement a risk-based breast cancer screening program in Spain. However, this poses a number of organizational and resource challenges.

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Background: Estimation of absolute risk of developing colorectal neoplasm is essential for personalized colorectal cancer (CRC) screening. We developed models to determine relative and absolute risks of colorectal neoplasm based on lifestyle and genetic variants and to validate their application in risk-adapted screening. Methods: We prospectively collected data from 203 advanced neoplasms, 464 non-advanced adenomas, and 1,213 healthy controls from a CRC screening trial in China in 2018-2019. The risk prediction model based on four lifestyle factors and a polygenic risk score (PRS) consisted of 19 CRC-associated single-nucleotide polymorphisms. We assessed the relative and 10-year absolute risks of developing colorectal neoplasm and the yield of a risk-adapted screening approach incorporating risk models, fecal immunochemical test, and colonoscopy. Results: Compared to the participants with favorable lifestyle and lower PRS, those with unfavorable lifestyle and higher PRS had 2.87- and 3.79-fold higher risk of colorectal neoplasm in males and females, respectively. For a 50-year-old man or a 50-year-old woman with the highest risk profile, the estimated 10-year absolute risk of developing colorectal neoplasm was 6.59% (95% CI: 6.53-6.65%) and 4.19% (95% CI: 4.11-4.28%), respectively, compared to 2.80% (95% CI: 2.78-2.81%) for men and 2.24% (95% CI: 2.21-2.27%) for women with the lowest risk profile. The positive predictive value for advanced neoplasm was 31.7%, and the number of colonoscopies needed to detect one advanced neoplasm was 3.2. Conclusion: The risk models, absolute risk estimates, and risk-adapted screening presented in our study would contribute to developing effective personalized CRC prevention and screening strategies.

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BACKGROUND: Fecal immunochemical testing (FIT) is an established method for colorectal cancer (CRC) screening. Measured FIT-concentrations are associated with both present and future risk of CRC, and may be used for personalized screening. However, evaluation of personalized screening is computationally challenging. In this study, a broadly applicable algorithm is presented to efficiently optimize personalized screening policies that prescribe screening intervals and FIT-cutoffs, based on age and FIT-history. METHODS: We present a mathematical framework for personalized screening policies and a bi-objective evolutionary algorithm that identifies policies with minimal costs and maximal health benefits. The algorithm is combined with an established microsimulation model (MISCAN-Colon), to accurately estimate the costs and benefits of generated policies, without restrictive Markov assumptions. The performance of the algorithm is demonstrated in three experiments. RESULTS: In Experiment 1, a relatively small benchmark problem, the optimal policies were known. The algorithm approached the maximum feasible benefits with a relative difference of 0.007%. Experiment 2 optimized both intervals and cutoffs, Experiment 3 optimized cutoffs only. Optimal policies in both experiments are unknown. Compared to policies recently evaluated for the USPSTF, personalized screening increased health benefits up to 14 and 4.3%, for Experiments 2 and 3, respectively, without adding costs. Generated policies have several features concordant with current screening recommendations. DISCUSSION: The method presented in this paper is flexible and capable of optimizing personalized screening policies evaluated with computationally-intensive but established simulation models. It can be used to inform screening policies for CRC or other diseases. For CRC, more debate is needed on what features a policy needs to exhibit to make it suitable for implementation in practice.

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The Cancer Registry of Norway has been administrating a national cervical cancer screening program since 1992 by coordinating triennial cytology exam screenings for the female population between 25 and 69 years of age. Up to 80% of cancers are prevented through mass screening, but this comes at the expense of considerable screening activity and leads to overtreatment of clinically asymptomatic precancers. In this article, we present a continuous-time, time-inhomogeneous hidden Markov model which was developed to understand the screening process and cervical cancer carcinogenesis in detail. By leveraging 1.7 million individual's multivariate time-series of medical exams performed over a 25-year period, we simultaneously estimate all model parameters. We show that an age-dependent model reflects the Norwegian screening program by comparing empirical survival curves from observed registry data and data simulated from the proposed model. The model can be generalized to include more detailed individual-level covariates as well as new types of screening exams. By utilizing individual screening histories and covariate data, the proposed model shows potential for improving strategies for cancer screening programs by personalizing recommended screening intervals.

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BACKGROUND: Although breast cancer screening reduces breast cancer mortality at the population level, subgroups of women may benefit differently. We investigated the impact of health status on the effect of breast cancer screening. METHODS: The study included 181 299 women invited in two population-based screening programs in Denmark and 1 526 446 control subjects, followed from April 1981 to December 2014. Poisson regressions were used to compare the observed breast cancer mortality rate in women invited to screening with the expected rate in the absence of screening among women with and without chronic diseases. Chronic diseases were defined as any diagnosis in the Charlson Comorbidity Index during 4 years before the first invitation to screening. RESULTS: Almost 10% of women had chronic diseases before first invitation to screening. Whereas we observed a reduction in breast cancer mortality following invitation to screening of 28% (95% CI, 20% to 35%) among women without chronic diseases, only a 7% (95% CI, -39% to 37%) reduction was seen for women with chronic diseases (P-value for interaction = .22). For participants, the reduction, corrected for selection bias, was 35% (95% CI 16% to 49%) for women without, and 4% (95% CI -146% to 62%) for women with chronic diseases (P-value for interaction = .43). CONCLUSION: Our data indicate a marginal effect of mammography screening on breast cancer mortality in women with chronic diseases. If our results are confirmed in other populations, the presence of chronic diseases will be an important factor to take into consideration in personalized screening.

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