Colorectal Cancer Screening - Approach, Evidence, and Future Directions

A Comprehensive Review of Artificial Intelligence and Colon Capsule Endoscopy: Opportunities and Challenges

Colon capsule endoscopy (CCE) enables a comprehensive, non-invasive, and painless evaluation of the colon, although it still has limited indications. The lengthy reading times hinder its wider implementation, a drawback that could potentially be overcome through the integration of artificial intelligence (AI) models. Studies employing AI, particularly convolutional neural networks (CNNs), demonstrate great promise in using CCE as a viable option for detecting certain diseases and alterations in the colon, compared to other methods like colonoscopy. Additionally, employing AI models in CCE could pave the way for a minimally invasive panenteric or even panendoscopic solution. This review aims to provide a comprehensive summary of the current state-of-the-art of AI in CCE while also addressing the challenges, both technical and ethical, associated with broadening indications for AI-powered CCE. Additionally, it also gives a brief reflection of the potential environmental advantages of using this method compared to alternative ones.

Changing colon cancer screening guidelines to age 45: Has it made a difference?

BACKGROUND

A concerning increase in early-onset colorectal cancer led to guideline changes in 2018 by the American Cancer Society to lower the age for initial colorectal cancer screening from 50 to 45 years of age. Although this would be expected to result in increased screening rates and subsequent earlier detection of colorectal cancer, the effect of this guideline change at a national level is not yet fully understood.

METHODS

Using the National Cancer Database, we identified patients newly targeted for screening (age 45-49 years) diagnosed with colon cancer in either 2017 (early cohort) or 2019 (late cohort). The relationship between time period and stage of disease at presentation was examined by univariate analysis and in a multivariable logistic regression model.

RESULTS

In total, 5,479 patients met inclusion criteria. The median age at diagnosis did not differ between patients in the late and early cohorts (47 years for both cohorts, P = .41). Patients in the late and early cohorts had equal odds of having stage III-IV disease (odds ratio for late cohort to early cohort, 1.05, 95% confidence interval, 0.94-1.17), and patients in the late cohort showed slightly increased odds of having higher T-stage (pT3 or pT4) disease (odds ratio, 1.20, 95% confidence interval, 1.05-1.35).

CONCLUSION

Despite recommendations of earlier initial colorectal cancer screening, a clinically meaningful earlier shift in colon cancer stage was not observed in patients newly targeted for screening. Further studies will be needed to assess uptake of these recommendations by providers and patients and identify areas of improvement.

Effect of computer aided detection device on the adenoma detection rate and serrated detection rate among trainee fellows

Background and Aims

The utilization of artificial intelligence (AI) with computer-aided detection (CADe) has the potential to increase the adenoma detection rate (ADR) by up to 30% in expert settings and specialized centers. The impact of CADe on serrated polyp detection rates (SDR) and academic trainees ADR & SDR remains underexplored. We aim to investigate the effect of CADe on ADR and SDR at an academic center with various levels of providers' experience.

Methods

A single-center retrospective analysis was conducted on asymptomatic patients between the ages of 45 and 75 who underwent screening colonoscopy. Colonoscopy reports were reviewed for 3 months prior to the introduction of GI Genius™ (Medtronic, USA) and 3 months after its implementation. The primary outcome was ADR and SDR with and without CADe.

Results

Totally 658 colonoscopies were eligible for analysis. CADe resulted in statistically significant improvement in SDR from 8.92% to 14.1% (P = 0.037). The (ADR + SDR) with CADe and without CADe was 58% and 55.1%, respectively (P = 0.46). Average colonoscopy (CSC) withdrawal time was 17.33 min (SD 10) with the device compared with 17.35 min (SD 9) without the device (P = 0.98).

Conclusion

In this study, GI Genius™ was associated with a statistically significant increase in SDR alone, but not in ADR or (ADR + SDR), likely secondary to the more elusive nature of serrated polyps compared to adenomatous polyps. The use of CADe did not affect withdrawal time.

Faecal immunochemical tests can improve colonoscopy triage in patients with iron deficiency: A systematic review and meta-analysis

BACKGROUND

Use of the faecal immunochemical test (FIT) to triage patients with iron deficiency (ID) for colonoscopy due to suspected colorectal cancer (CRC) may improve distribution of colonoscopic resources. We reviewed the diagnostic performance of FIT for detecting advanced colorectal neoplasia, including CRC and advanced pre-cancerous neoplasia (APCN), in patients with ID, with or without anaemia.

METHODS

We performed a systematic review of three databases for studies comprising of patients with ID, with or without anaemia, completing a quantitative FIT within six months prior to colonoscopy, where test performance was compared against the reference standard colonoscopy. Random effects meta-analyses determined the diagnostic performance of FIT for advanced colorectal neoplasia.

RESULTS

Nine studies were included on a total of n=1761 patients with ID, reporting FIT positivity thresholds between 4-150 µg haemoglobin/g faeces. Only one study included a non-anaemic ID (NAID) cohort. FIT detected CRC and APCN in ID patients with 90.7 % and 49.3 % sensitivity, and 81.0 % and 82.4 % specificity, respectively. FIT was 88.0 % sensitive and 83.4 % specific for CRC in patients with ID anaemia at a FIT positivity threshold of 10 µg haemoglobin/g faeces.

CONCLUSIONS

FIT shows high sensitivity for advanced colorectal neoplasia and may be used to triage those with ID anaemia where colonoscopic resources are limited, enabling those at higher risk of CRC to be prioritised for colonoscopy. There is a need for further research investigating the diagnostic performance of FIT in NAID patients.

Barriers in early detection of colorectal cancer and exploring potential solutions

This editorial discusses the literature review article by Tonini and Zanni, the paper was published in January 2024, and the authors provided very interesting conclusions regarding existing barriers to the early diagnosis of colon cancer. Many cancers do not have identifiable precursors, or there are currently no screening tests to find them. Therefore, these cancers do not have preventive screening options. Early detection is crucial for reducing mortality rates by identifying cancer at an earlier stage through screening, as opposed to no screening. Colorectal cancer develops from precancerous lesions, which can be detected early and potentially prevented and cured. Early detection leads to improved survival rates, decreased complications, and reduced healthcare expenses. This editorial provides a brief description of the biology of colon cancer, emphasizing the contrast in outcomes between early detection and late detection. We also describe screening programs around the globe and examine the barriers in each program. Finally, we explore potential future solutions to enhance inclusion in screening programs and improve patient compliance.

Colorectal cancer

Despite decreased incidence rates in average-age onset patients in high-income economies, colorectal cancer is the third most diagnosed cancer in the world, with increasing rates in emerging economies. Furthermore, early onset colorectal cancer (age ≤50 years) is of increasing concern globally. Over the past decade, research advances have increased biological knowledge, treatment options, and overall survival rates. The increase in life expectancy is attributed to an increase in effective systemic therapy, improved treatment selection, and expanded locoregional surgical options. Ongoing developments are focused on the role of sphincter preservation, precision oncology for molecular alterations, use of circulating tumour DNA, analysis of the gut microbiome, as well as the role of locoregional strategies for colorectal cancer liver metastases. This overview is to provide a general multidisciplinary perspective of clinical advances in colorectal cancer.

Distinctive Lipid Characteristics of Colorectal Cancer Revealed through Non-targeted Lipidomics Analysis of Tongue Coating

The metabolites and microbiota in tongue coating display distinct characteristics in certain digestive disorders, yet their relationship with colorectal cancer (CRC) remains unexplored. Here, we employed liquid chromatography coupled with tandem mass spectrometry to analyze the lipid composition of tongue coating using a nontargeted approach in 30 individuals with colorectal adenomas (CRA), 32 with CRC, and 30 healthy controls (HC). We identified 21 tongue coating lipids that effectively distinguished CRC from HC (AUC = 0.89), and 9 lipids that differentiated CRC from CRA (AUC = 0.9). Furthermore, we observed significant alterations in the tongue coating lipid composition in the CRC group compared to HC/CRA groups. As the adenoma-cancer sequence progressed, there was an increase in long-chain unsaturated triglycerides (TG) levels and a decrease in phosphatidylethanolamine plasmalogen (PE-P) levels. Furthermore, we noted a positive correlation between N-acyl ornithine (NAOrn), sphingomyelin (SM), and ceramide phosphoethanolamine (PE-Cer), potentially produced by members of the Bacteroidetes phylum. The levels of inflammatory lipid metabolite 12-HETE showed a decreasing trend with colorectal tumor progression, indicating the potential involvement of tongue coating microbiota and tumor immune regulation in early CRC development. Our findings highlight the potential utility of tongue coating lipid analysis as a noninvasive tool for CRC diagnosis.

Deep learning for colorectal cancer detection in contrast-enhanced CT without bowel preparation: a retrospective, multicentre study

BACKGROUND

Contrast-enhanced CT scans provide a means to detect unsuspected colorectal cancer. However, colorectal cancers in contrast-enhanced CT without bowel preparation may elude detection by radiologists. We aimed to develop a deep learning (DL) model for accurate detection of colorectal cancer, and evaluate whether it could improve the detection performance of radiologists.

METHODS

We developed a DL model using a manually annotated dataset (1196 cancer vs 1034 normal). The DL model was tested using an internal test set (98 vs 115), two external test sets (202 vs 265 in 1, and 252 vs 481 in 2), and a real-world test set (53 vs 1524). We compared the detection performance of the DL model with radiologists, and evaluated its capacity to enhance radiologists' detection performance.

FINDINGS

In the four test sets, the DL model had the area under the receiver operating characteristic curves (AUCs) ranging between 0.957 and 0.994. In both the internal test set and external test set 1, the DL model yielded higher accuracy than that of radiologists (97.2% vs 86.0%, p < 0.0001; 94.9% vs 85.3%, p < 0.0001), and significantly improved the accuracy of radiologists (93.4% vs 86.0%, p < 0.0001; 93.6% vs 85.3%, p < 0.0001). In the real-world test set, the DL model delivered sensitivity comparable to that of radiologists who had been informed about clinical indications for most cancer cases (94.3% vs 96.2%, p > 0.99), and it detected 2 cases that had been missed by radiologists.

INTERPRETATION

The developed DL model can accurately detect colorectal cancer and improve radiologists' detection performance, showing its potential as an effective computer-aided detection tool.

FUNDING

This study was supported by National Science Fund for Distinguished Young Scholars of China (No. 81925023); Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (No. U22A20345); National Natural Science Foundation of China (No. 82072090 and No. 82371954); Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No. 2022B1212010011); High-level Hospital Construction Project (No. DFJHBF202105).

Prevalence of colonoscopy in Japan using a large-scale health claims data compared to esophagogastroduodenoscopy

OBJECTIVE

Prevalence of colonoscopy (CS) is an important countermeasure against colorectal cancer (CRC). In this study, we used large-scale data for a comparison of CS with esophagogastroduodenoscopy (EGD) in Japan.

METHODS

This was a retrospective descriptive study. Commercially anonymized patient data were collected from various health insurance societies (JMDC, Inc. Tokyo, Japan) generated from the insurance registry, receipts (inpatient, outpatient, and prescription), and health checkup data. The data also included healthy subjects who had never been examined in a hospital. The data of 2,760,048 persons who were 50-75 years old during January 2012-December 2019 were extracted from the original data source. The annual rate, the prevalence rate (frequency of those undergoing at least one endoscopy during the period), and the percentage of repeaters (undergoing endoscopy at least twice during the period) of CS were calculated and compared to those of EGD.

RESULTS

The annual rates in 2012/2015/2019 were 3.4%/4.5%/5.3% for CS, respectively, and increased gradually from 2012 to 2019. Those rates were 7.0%/7.9%/7.4% for EGD, respectively, and did not increase. The prevalence rates of CS and EGD were 25.3% and 36.2%, respectively, among the 137,246 participants over 8 years. The prevalence rates of individuals in their 50 s/60 s/70 s were 23.0%/25.9%/31.4% for CS and 33.0%/37.6%/40.7% for EGD, respectively. The proportions of males/females were 27.9%/20.7% for CS, and 36.4%/35.8% for EGD, respectively. The repeat rates of CS and EGD were 40.3% and 44.8%, respectively, over 8 years.

CONCLUSIONS

Using large-scale data, we determined the status of CS and EGD in Japan.

Pathological Insights: Enhanced Vision Transformers for the Early Detection of Colorectal Cancer

Endoscopic pathological findings of the gastrointestinal tract are crucial for the early diagnosis of colorectal cancer (CRC). Previous deep learning works, aimed at improving CRC detection performance and reducing subjective analysis errors, are limited to polyp segmentation. Pathological findings were not considered and only convolutional neural networks (CNNs), which are not able to handle global image feature information, were utilized. This work introduces a novel vision transformer (ViT)-based approach for early CRC detection. The core components of the proposed approach are ViTCol, a boosted vision transformer for classifying endoscopic pathological findings, and PUTS, a vision transformer-based model for polyp segmentation. Results demonstrate the superiority of this vision transformer-based CRC detection method over existing CNN and vision transformer models. ViTCol exhibited an outstanding performance in classifying pathological findings, with an area under the receiver operating curve (AUC) value of 0.9999 ± 0.001 on the Kvasir dataset. PUTS provided outstanding results in segmenting polyp images, with mean intersection over union (mIoU) of 0.8673 and 0.9092 on the Kvasir-SEG and CVC-Clinic datasets, respectively. This work underscores the value of spatial transformers in localizing input images, which can seamlessly integrate into the main vision transformer network, enhancing the automated identification of critical image features for early CRC detection.

The microbial landscape of colorectal cancer

Colorectal cancer (CRC) is a substantial source of global morbidity and mortality in dire need of improved prevention and treatment strategies. As our understanding of CRC grows, it is becoming increasingly evident that the gut microbiota, consisting of trillions of microorganisms in direct interface with the colon, plays a substantial role in CRC development and progression. Understanding the roles that individual microorganisms and complex microbial communities play in CRC pathogenesis, along with their attendant mechanisms, will help yield novel preventive and therapeutic interventions for CRC. In this Review, we discuss recent evidence concerning global perturbations of the gut microbiota in CRC, associations of specific microorganisms with CRC, the underlying mechanisms by which microorganisms potentially drive CRC development and the roles of complex microbial communities in CRC pathogenesis. While our understanding of the relationship between the microbiota and CRC has improved in recent years, our findings highlight substantial gaps in current research that need to be filled before this knowledge can be used to the benefit of patients.

Longer Colonoscopy Withdrawal Time Is Associated With the Detection of Visible Dysplasia in Patients With Inflammatory Bowel Disease

Background

Colonoscopy withdrawal time (CWT) of at least 6-9 minutes is the minimum time needed for adequate adenoma detection in the general population. The ideal CWT in patients with inflammatory bowel disease (IBD) has not been determined. We aimed to identify the optimal CWT associated with the detection of visible dysplasia in patients with IBD.

Methods

This is a retrospective study from 1/1/2017 to 9/1/2022 of adult patients with IBD in endoscopic healing undergoing surveillance via high-definition white light colonoscopy. The primary outcome was the association of CWT with visible dysplasia detection.

Results

A total of 259 patients (mean age 56 ± 14.8 years; 51.3% female, 68% with ulcerative colitis; 8.9% with primary sclerosing cholangitis) underwent 330 colonoscopies. Patients with visible dysplasia were more likely to be older (P < .001) and have a personal history of visible dysplasia (P < .001) and invisible dysplasia (P = .023). The mean CWT was significantly longer in the visible dysplasia group at 26 minutes (interquartile range [IQR] 20-38.5) vs. 21 minutes (IQR 15-28) in procedures without visible dysplasia (P < .001). On multivariable analysis, increased age (P < .001), increased CWT (P = .001), and personal history of visible dysplasia (P = .013) were independently associated with the detection of visible dysplasia. A CWT of ≥15 minutes (odds ratio [OR] 2.71; 95% confidence interval [CI], 1.11-6.6; P = .02] and not ≥9 minutes (OR 2.57; 95% CI, 0.33-20.2; P = .35) is significantly associated with detection of visible dysplasia.

Conclusions

For patients with IBD undergoing surveillance via high-definition white light colonoscopy, the mean CWT was independently associated with the detection of visible dysplasia.

GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review

Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.

Fecal Immunochemical Testing and the Risk of Advanced Colorectal Neoplasia: A Difference-In-Difference Analysis

PURPOSE

To evaluate the effectiveness of fecal immunochemical testing (FIT) in colorectal cancer screening.

METHODS

We conducted a prospective cohort study among 5,598 participants age 40-74 years between 2012 and 2020 in Tianjin, China. Inverse probability weighting was adopted to adjust for potential imbalanced factors between groups. A Cox proportional hazards model was used to estimate the weighted associations between FIT screening and advanced colorectal neoplasia. A difference-in-difference (DID) model was adopted to compare the incidence rates of advanced colorectal neoplasia between groups.

RESULTS

In DID analysis, the rate of incidence was reduced by 0.34 cases per person-years in the screening group as compared with the historical FIT screening group (rate ratio [RR], 0.08 [95% CI, 0.07 to 0.10]) and by 0.06 cases per person-years in the non-FIT screening group as compared with the historical non-FIT screening group (RR, 0.37 [95% CI, 0.29 to 0.48]; P < .001 for both comparisons), with a relative reduction of 0.28. Similar benefit effect from FIT screening was observed in sex and age subgroups.

CONCLUSION

FIT screening was associated with a reduction in incidence density from advanced colorectal neoplasia.

Anti-Proliferative and Apoptotic Activities of Rumex crispus

Colorectal cancer is the fourth leading cause of cancer death and the third most common cancer diagnosed in the United States. Several anticancer compounds from natural products have been of great interest in cancer chemotherapy and are currently in clinical trials. Natural products that present the targeted killing of cancerous cell and are soluble in water with minimal side effects are ideal candidates. In this study, water-soluble compounds from Rumex crispus plants were screened for anti-proliferative and apoptotic activity against human colorectal adenocarcinoma (DLD-1) cells. The most potent fraction with the highest cell killing and caspase fold change rates was selected for further experiments. The observed changes were further validated by measuring the caspase fold change using RT-qPCR. Furthermore, gene transcript levels were evaluated using an RT2 Profiler assay and a microarray experiment. Our results showed that the most potent L19 fraction exhibits anti-proliferative activity in a dose-dependent manner. The L19 fraction was found to induce apoptotic pathways by triggering different caspases and inflammatory pathways through the activation of non-apoptotic genes. Our study identified and validated the anticancer property of the L19 fraction, which can serve as a strong lead compound for the synthesis of other novel potent analogues.

The Impact of a Six-Year Existing Screening Programme Using the Faecal Immunochemical Test in Flanders (Belgium) on Colorectal Cancer Incidence, Mortality and Survival: A Population-Based Study

The faecal immunochemical test (FIT) has been increasingly used for organised colorectal cancer (CRC) screening. We assessed the impact of a six-year existing FIT screening programme in Flanders (Belgium) on CRC incidence, mortality and survival. The Flemish CRC screening programme started in 2013, targeting individuals aged 50-74 years. Joinpoint regression was used to investigate trends of age-standardised CRC incidence and mortality among individuals aged 50-79 years (2004-2019). Their 5-year relative survival was calculated using the Ederer II method. We found that FIT screening significantly reduced CRC incidence, especially that of advanced-stage CRCs (69.8/100,000 in 2012 vs. 51.1/100,000 in 2019), with a greater impact in men. Mortality started to decline in men two years after organised screening implementation (annual reduction of 9.3% after 2015 vs. 2.2% before 2015). The 5-year relative survival was significantly higher in screen-detected (93.8%) and lower in FIT non-participant CRCs (61.9%) vs. FIT interval cancers and CRCs in never-invited cases (67.6% and 66.7%, respectively). Organised FIT screening in Flanders clearly reduced CRC incidence (especially advanced-stage) and mortality (in men, but not yet in women). Survival is significantly better in screen-detected cases vs. CRCs in unscreened people. Our findings support the implementation of FIT organised screening and the continued effort to increase uptake.

Recent Advancements, Limitations, and Future Perspectives of the use of Personalized Medicine in Treatment of Colon Cancer

Due to the heterogeneity of colon cancer, surgery, chemotherapy, and radiation are ineffective in all cases. The genomic profile and biomarkers associated with the process are considered in personalized medicine, along with the patient's personal history. It is based on the response of the targeted therapies to specific genetic variations. The patient's genetic transcriptomic and epigenetic features are evaluated, and the best therapeutic approach and diagnostic testing are identified through personalized medicine. This review aims to summarize all the necessary, updated information on colon cancer related to personalized medicine. Personalized medicine is gaining prominence as generalized treatments are finding it challenging to contain colon cancer cases which currently rank fourth among global cancer incidence while being the fifth largest in total death cases worldwide. In personalized therapy, patients are grouped into specific categories, and the best therapeutic approach is chosen based on evaluating their molecular features. Various personalized strategies are currently being explored in the treatment of colon cancer involving immunotherapy, phytochemicals, and other biomarker-specific targeted therapies. However, significant challenges must be overcome to integrate personalized medicine into healthcare systems completely. We look at the various signaling pathways and genetic and epigenetic alterations associated with colon cancer to understand and identify biomarkers useful in targeted therapy. The current personalized therapies available in colon cancer treatment and the strategies being explored to improve the existing methods are discussed. This review highlights the advantages and limitations of personalized medicine in colon cancer therapy. The current scenario of personalized medicine in developed countries and the challenges faced in middle- and low-income countries are also summarized. Finally, we discuss the future perspectives of personalized medicine in colon cancer and how it could be integrated into the healthcare systems.

Circulating Tumor DNA-A Novel Biomarker of Tumor Progression and Its Favorable Detection Techniques

Cancer is the second leading cause of death in the world and seriously affects the quality of life of patients. The diagnostic techniques for tumors mainly include tumor biomarker detection, instrumental examination, and tissue biopsy. In recent years, liquid technology represented by circulating tumor DNA (ctDNA) has gradually replaced traditional technology with its advantages of being non-invasive and accurate, its high specificity, and its high sensitivity. ctDNA may carry throughout the circulatory system through tumor cell necrosis, apoptosis, circulating exosome secretion, etc., carrying the characteristic changes in tumors, such as mutation, methylation, microsatellite instability, gene rearrangement, etc. In this paper, ctDNA mutation and methylation, as the objects to describe the preparation process before ctDNA analysis, and the detection methods of two gene-level changes, including a series of enrichment detection techniques derived from PCR, sequencing-based detection techniques, and comprehensive detection techniques, are combined with new materials. In addition, the role of ctDNA in various stages of cancer development is summarized, such as early screening, diagnosis, molecular typing, prognosis prediction, recurrence monitoring, and drug guidance. In summary, ctDNA is an ideal biomarker involved in the whole process of tumor development.

Simulation of a machine learning enabled learning health system for risk prediction using synthetic patient data

When enabled by machine learning (ML), Learning Health Systems (LHS) hold promise for improving the effectiveness of healthcare delivery to patients. One major barrier to LHS research and development is the lack of access to EHR patient data. To overcome this challenge, this study demonstrated the feasibility of developing a simulated ML-enabled LHS using synthetic patient data. The ML-enabled LHS was initialized using a dataset of 30,000 synthetic Synthea patients and a risk prediction XGBoost base model for lung cancer. 4 additional datasets of 30,000 patients were generated and added to the previous updated dataset sequentially to simulate addition of new patients, resulting in datasets of 60,000, 90,000, 120,000 and 150,000 patients. New XGBoost models were built in each instance, and performance improved with data size increase, attaining 0.936 recall and 0.962 AUC (area under curve) in the 150,000 patients dataset. The effectiveness of the new ML-enabled LHS process was verified by implementing XGBoost models for stroke risk prediction on the same Synthea patient populations. By making the ML code and synthetic patient data publicly available for testing and training, this first synthetic LHS process paves the way for more researchers to start developing LHS with real patient data.

[PAPPS Expert Groups. Cancer prevention recommendations: Update 2022]

Cancer is a major cause of morbidity and mortality. Tobacco use, unhealthy diet, and physical inactivity are some of the lifestyle risk factors that have led to an increase in cancer. This article updates the evidence and includes recommendations for prevention strategies for each of the cancers with the highest incidence. These are based on the reduction of risk factors (primary prevention) and early diagnosis of cancer through screening and early detection of signs and symptoms, in medium-risk and high-risk populations. This update of the 2022 PAPPS has taken into account the vision of the National Health System Cancer Strategy, an update approved by the Interterritorial Council of the National Health System on January 2021 and the European Strategy (Europe's Beating Cancer Plan) presented on 4 February 2021.