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In this randomized trial involving 84,585 participants in Poland, Norway, and Sweden, the risk of colorectal cancer at 10 years was lower among those invited to undergo screening colonoscopy than among those assigned to no screening.

\"This powerful new volume explores the diverse and sometimes unexpected roles that IoT and AI technologies played during the recent COVID-19 global pandemic. The book discusses the how existing and new state-of-the art technology has been and can be applied for global health crises in a multitude of ways. The chapters in Pandemic Detection and Analysis through Smart Computing Technologies look at exciting technological solutions for virus detection, prediction, classification, prevention, and communication outreach. The book considers the various modes of transmission of the virus as well as how technology has been implemented for personalized healthcare systems and how it can be used for future pandemics. The huge importance of social and mobile communication and networks during the pandemic in diverse ways is addressed such as in business, education, and healthcare; in research and development; for health information and outreach; in social life; and more. A chapter also addresses using smart computing for forecasting the damage caused by COVID-19 using time series analyses. This up-to-the-minute volume illuminates on the many ways AI, IoT, machine learning, and other technologies have important roles in the diverse challenges faced during COVID-19 and how they can be enhanced for future pandemic situations. The volume will be of high interest to those in different fields of computer science and other domains as well as to data scientists, government agencies and policymakers, doctors and healthcare professionals, engineers, economists, and many other professionals. This book will also be very helpful to faculty, students, and research scholars in understanding the pre- and post-effect of this pandemic\"-- Provided by publisher.

After 4 years of the GÖTEBORG-2 trial, MRI-targeted biopsy led to less detection of clinically insignificant prostate cancer than systematic biopsy without compromising the detection of cancer that may affect survival.

In four randomised trials, human papillomavirus (HPV)-based screening for cervical cancer was compared with cytology-based cervical screening, and precursors of cancer were the endpoint in every trial. However, direct estimates are missing of the relative efficacy of HPV-based versus cytology-based screening for prevention of invasive cancer in women who undergo regular screening, of modifiers (eg, age) of this relative efficacy, and of the duration of protection. We did a follow-up study of the four randomised trials to investigate these outcomes. 176 464 women aged 20–64 years were randomly assigned to HPV-based (experimental arm) or cytology-based (control arm) screening in Sweden (Swedescreen), the Netherlands (POBASCAM), England (ARTISTIC), and Italy (NTCC). We followed up these women for a median of 6·5 years (1 214 415 person-years) and identified 107 invasive cervical carcinomas by linkage with screening, pathology, and cancer registries, by masked review of histological specimens, or from reports. Cumulative and study-adjusted rate ratios (experimental vs control) were calculated for incidence of invasive cervical carcinoma. The rate ratio for invasive cervical carcinoma among all women from recruitment to end of follow-up was 0·60 (95% CI 0·40–0·89), with no heterogeneity between studies (p=0·52). Detection of invasive cervical carcinoma was similar between screening methods during the first 2·5 years of follow-up (0·79, 0·46–1·36) but was significantly lower in the experimental arm thereafter (0·45, 0·25–0·81). In women with a negative screening test at entry, the rate ratio was 0·30 (0·15–0·60). The cumulative incidence of invasive cervical carcinoma in women with negative entry tests was 4·6 per 105 (1·1–12·1) and 8·7 per 105 (3·3–18·6) at 3·5 and 5·5 years, respectively, in the experimental arm, and 15·4 per 105 (7·9–27·0) and 36·0 per 105 (23·2–53·5), respectively, in the control arm. Rate ratios did not differ by cancer stage, but were lower for adenocarcinoma (0·31, 0·14–0·69) than for squamous-cell carcinoma (0·78, 0·49–1·25). The rate ratio was lowest in women aged 30–34 years (0·36, 0·14–0·94). HPV-based screening provides 60–70% greater protection against invasive cervical carcinomas compared with cytology. Data of large-scale randomised trials support initiation of HPV-based screening from age 30 years and extension of screening intervals to at least 5 years. European Union, Belgian Foundation Against Cancer, KCE-Centre d'Expertise, IARC, The Netherlands Organisation for Health Research and Development, the Italian Ministry of Health.

Abstract Rationale Screening for lung cancer with low-dose spiral computed tomography (LDCT) has been shown to reduce lung cancer mortality by 20% compared with screening with chest X-ray (CXR) in the National Lung Screening Trial, but uncertainty remains concerning the efficacy of LDCT screening in a community setting. Objectives To explore the effect of LDCT screening on lung cancer mortality compared with no screening. Secondary endpoints included incidence, stage, and resectability rates. Methods Male smokers of 20+ pack-years, aged 60 to 74 years, underwent a baseline CXR and sputum cytology examination and received five screening rounds with LDCT or a yearly clinical review only in a randomized fashion. Measurements and Main Results A total of 1,264 subjects were enrolled in the LDCT arm and 1,186 in the control arm. Their median age was 64.0 years (interquartile range, 5), and median smoking exposure was 45.0 pack-years. The median follow-up was 8.35 years. One hundred four patients (8.23%) were diagnosed with lung cancer in the screening arm (66 by CT), 47 of whom (3.71%) had stage I disease; 72 control patients (6.07%) were diagnosed with lung cancer, with 16 (1.35%) being stage I cases. Lung cancer mortality was 543 per 100,000 person-years (95% confidence interval, 413–700) in the LDCT arm versus 544 per 100,000 person-years (95% CI, 410–709) in the control arm (hazard ratio, 0.993; 95% confidence interval, 0.688–1.433). Conclusions Because of its limited statistical power, the results of the DANTE (Detection And screening of early lung cancer with Novel imaging TEchnology) trial do not allow us to make a definitive statement about the efficacy of LDCT screening. However, they underline the importance of obtaining additional data from randomized trials with intervention-free reference arms before the implementation of population screening.

Screening mammography reduces breast cancer mortality, but studies analyzing interval cancers diagnosed after negative screens have shown that many cancers are missed. Supplemental screening using magnetic resonance imaging (MRI) can reduce the number of missed cancers. However, as qualified MRI staff are lacking, the equipment is expensive to purchase and cost-effectiveness for screening may not be convincing, the utilization of MRI is currently limited. An effective method for triaging individuals to supplemental MRI screening is therefore needed. We conducted a randomized clinical trial, ScreenTrustMRI, using a recently developed artificial intelligence (AI) tool to score each mammogram. We offered trial participation to individuals with a negative screening mammogram and a high AI score (top 6.9%). Upon agreeing to participate, individuals were assigned randomly to one of two groups: those receiving supplemental MRI and those not receiving MRI. The primary endpoint of ScreenTrustMRI is advanced breast cancer defined as either interval cancer, invasive component larger than 15 mm or lymph node positive cancer, based on a 27-month follow-up time from the initial screening. Secondary endpoints, prespecified in the study protocol to be reported before the primary outcome, include cancer detected by supplemental MRI, which is the focus of the current paper. Compared with traditional breast density measures used in a previous clinical trial, the current AI method was nearly four times more efficient in terms of cancers detected per 1,000 MRI examinations (64 versus 16.5). Most additional cancers detected were invasive and several were multifocal, suggesting that their detection was timely. Altogether, our results show that using an AI-based score to select a small proportion (6.9%) of individuals for supplemental MRI after negative mammography detects many missed cancers, making the cost per cancer detected comparable with screening mammography. ClinicalTrials.gov registration: NCT04832594 . In an interim analysis, an artificial intelligence model was nearly four times more efficient in terms of cancers detected per number of magnetic resonance imaging tests, compared to traditional breast density measures used in a previous clinical trial.

The PLCO trial generated data that argue against PSA screening. However, participants in the control group also reported being screened. An analysis of health questionnaires suggests that more than 80% of controls had been tested within the previous 3 years. To the Editor: In March, the Centers for Medicare and Medicaid Services temporarily suspended the development of a proposed “Non-Recommended Prostate-Specific Antigen (PSA)–Based Screening” measure that would discourage PSA screening in all men. The U.S. Preventive Services Task Force (USPSTF) is currently in the process of updating its recommendations for prostate-cancer screening. The decisions made by these two organizations are likely to determine the fate of PSA screening in the United States. Much of the controversy surrounding screening revolves around the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, which randomly assigned men to annual prostate-cancer screening or usual . . .

Retrospective studies have shown promising results using artificial intelligence (AI) to improve mammography screening accuracy and reduce screen-reading workload; however, to our knowledge, a randomised trial has not yet been conducted. We aimed to assess the clinical safety of an AI-supported screen-reading protocol compared with standard screen reading by radiologists following mammography. In this randomised, controlled, population-based trial, women aged 40–80 years eligible for mammography screening (including general screening with 1·5–2-year intervals and annual screening for those with moderate hereditary risk of breast cancer or a history of breast cancer) at four screening sites in Sweden were informed about the study as part of the screening invitation. Those who did not opt out were randomly allocated (1:1) to AI-supported screening (intervention group) or standard double reading without AI (control group). Screening examinations were automatically randomised by the Picture Archive and Communications System with a pseudo-random number generator after image acquisition. The participants and the radiographers acquiring the screening examinations, but not the radiologists reading the screening examinations, were masked to study group allocation. The AI system (Transpara version 1.7.0) provided an examination-based malignancy risk score on a 10-level scale that was used to triage screening examinations to single reading (score 1–9) or double reading (score 10), with AI risk scores (for all examinations) and computer-aided detection marks (for examinations with risk score 8–10) available to the radiologists doing the screen reading. Here we report the prespecified clinical safety analysis, to be done after 80 000 women were enrolled, to assess the secondary outcome measures of early screening performance (cancer detection rate, recall rate, false positive rate, positive predictive value [PPV] of recall, and type of cancer detected [invasive or in situ]) and screen-reading workload. Analyses were done in the modified intention-to-treat population (ie, all women randomly assigned to a group with one complete screening examination, excluding women recalled due to enlarged lymph nodes diagnosed with lymphoma). The lowest acceptable limit for safety in the intervention group was a cancer detection rate of more than 3 per 1000 participants screened. The trial is registered with ClinicalTrials.gov, NCT04838756, and is closed to accrual; follow-up is ongoing to assess the primary endpoint of the trial, interval cancer rate. Between April 12, 2021, and July 28, 2022, 80 033 women were randomly assigned to AI-supported screening (n=40 003) or double reading without AI (n=40 030). 13 women were excluded from the analysis. The median age was 54·0 years (IQR 46·7–63·9). Race and ethnicity data were not collected. AI-supported screening among 39 996 participants resulted in 244 screen-detected cancers, 861 recalls, and a total of 46 345 screen readings. Standard screening among 40 024 participants resulted in 203 screen-detected cancers, 817 recalls, and a total of 83 231 screen readings. Cancer detection rates were 6·1 (95% CI 5·4–6·9) per 1000 screened participants in the intervention group, above the lowest acceptable limit for safety, and 5·1 (4·4–5·8) per 1000 in the control group—a ratio of 1·2 (95% CI 1·0–1·5; p=0·052). Recall rates were 2·2% (95% CI 2·0–2·3) in the intervention group and 2·0% (1·9–2·2) in the control group. The false positive rate was 1·5% (95% CI 1·4–1·7) in both groups. The PPV of recall was 28·3% (95% CI 25·3–31·5) in the intervention group and 24·8% (21·9–28·0) in the control group. In the intervention group, 184 (75%) of 244 cancers detected were invasive and 60 (25%) were in situ; in the control group, 165 (81%) of 203 cancers were invasive and 38 (19%) were in situ. The screen-reading workload was reduced by 44·3% using AI. AI-supported mammography screening resulted in a similar cancer detection rate compared with standard double reading, with a substantially lower screen-reading workload, indicating that the use of AI in mammography screening is safe. The trial was thus not halted and the primary endpoint of interval cancer rate will be assessed in 100 000 enrolled participants after 2-years of follow up. Swedish Cancer Society, Confederation of Regional Cancer Centres, and the Swedish governmental funding for clinical research (ALF).

High-risk persons were screened for lung cancer in a population-based, randomized, controlled trial that involved volume-based nodule management for further testing. At 10 years of follow-up, lung-cancer mortality was significantly lower in the screening group than in the control group (2.5 vs. 3.3 per 1000 person-years among male participants).