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Background Multiple quality metrics have been recommended to ensure consistent, high-quality execution of screening tests for breast, cervical, colorectal, and lung cancers. However, minimal data exist evaluating the evidence base supporting these recommendations and the consistency of definitions and concepts included within and between cancer types. Methods We performed a systematic review for each cancer type using MEDLINE, Embase, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) from 2010 to April 2020 to identify guidelines from screening programs or professional organizations containing quality metrics for tests used in breast, cervical, colorectal, and lung cancer screening. We abstracted metrics’ definitions, target performance levels, and related supporting evidence for test completeness, adequacy (sufficient visualization or collection), accuracy, and safety. Results We identified 11 relevant guidelines with 20 suggested quality metrics for breast cancer, 5 guidelines with 9 metrics for cervical cancer, 13 guidelines with 18 metrics for colorectal cancer (CRC), and 3 guidelines with 7 metrics for lung cancer. These included 54 metrics related to adequacy (n = 6), test completeness (n = 3), accuracy (n = 33), and safety (n = 12). Target performance levels were defined for 30 metrics (56%). Ten (19%) were supported by evidence, all from breast and CRC, with no evidence cited to support metrics from cervical and lung cancer screening. Conclusions Considerably more guideline-recommended test performance metrics exist for breast and CRC screening than cervical or lung cancer. The domains covered are inconsistent among cancers, and few targets are supported by evidence. Clearer evidence-based domains and targets are needed for test performance metrics. Registration PROSPERO 2020 CRD42020179139

The U.S. Preventive Services Task Force recommends breast, cervical, and colorectal cancer screening to reduce mortality from these cancers, but screening use has been below national targets. The purpose of this study is to examine the proportion of screening-eligible adults who are up to date with these screenings and how screening use compares with Healthy People 2020 targets.Data from the 2019 National Health Interview Survey were used to examine the percentages of adults up to date with breast cancer screening among women aged 50‒74 years without previous breast cancer, cervical cancer screening among women aged 21‒65 years without previous cervical cancer or hysterectomy, and colorectal cancer screening among adults aged 50‒75 years without previous colorectal cancer. Estimates are presented by sociodemographic characteristics and healthcare access factors. Analyses were conducted in 2021.Percentages of adults up to date were 76.2% (95% CI= 75.0, 77.5) for breast cancer screening, 76.4% (95% CI= 75.2, 77.6) for cervical cancer screening, and 68.3% (95% CI= 67.3, 69.3) for colorectal cancer screening. Although some population subgroups met breast and colorectal cancer screening targets (81.1% and 70.5%, respectively), many did not, and cervical cancer screening was below the target for all examined subgroups. Lower education and income, nonmetropolitan county of residence (which included rural counties), no usual source of care or health insurance coverage, and Medicaid coverage were associated with lower screening test use.Estimated use of breast, cervical, and colorectal cancer screening tests based on the 2019 National Health Interview Survey were below national targets. Continued monitoring may allow for examination of screening trends, inform interventions, and track progress in eliminating disparities.

BACKGROUND: Preterm birth is a global health priority. Using a progestogen during high-risk pregnancy could reduce preterm birth and adverse neonatal outcomes.METHODS: We did a systematic review of randomised trials comparing vaginal progesterone, intramuscular 17-hydroxyprogesterone caproate (17-OHPC), or oral progesterone with control, or with each other, in asymptomatic women at risk of preterm birth. We identified published and unpublished trials that completed primary data collection before July 30, 2016, (12 months before data collection began), by searching MEDLINE, Embase, CINAHL, the Maternity and Infant Care Database, and relevant trial registers between inception and July 30, 2019. Trials of progestogen to prevent early miscarriage or immediately-threatened preterm birth were excluded. Individual participant data were requested from investigators of eligible trials. Outcomes included preterm birth, early preterm birth, and mid-trimester birth. Adverse neonatal sequelae associated with early births were assessed using a composite of serious neonatal complications, and individually. Adverse maternal outcomes were investigated as a composite and individually. Individual participant data were checked and risk of bias assessed independently by two researchers. Primary meta-analyses used one-stage generalised linear mixed models that incorporated random effects to allow for heterogeneity across trials. This meta-analysis is registered with PROSPERO, CRD42017068299.FINDINGS: Initial searches identified 47 eligible trials. Individual participant data were available for 30 of these trials. An additional trial was later included in a targeted update. Data were therefore available from a total of 31 trials (11 644 women and 16185 offspring). Trials in singleton pregnancies included mostly women with previous spontaneous preterm birth or short cervix. Preterm birth before 34 weeks was reduced in such women who received vaginal progesterone (nine trials, 3769 women; relative risk [RR] 0·78, 95% CI 0·68-0·90), 17-OHPC (five trials, 3053 women; 0·83, 0·68-1·01), and oral progesterone (two trials, 181 women; 0·60, 0·40-0·90). Results for other birth and neonatal outcomes were consistently favourable, but less certain. A possible increase in maternal complications was suggested, but this was uncertain. We identified no consistent evidence of treatment interaction with any participant characteristics examined, although analyses within subpopulations questioned efficacy in women who did not have a short cervix. Trials in multifetal pregnancies mostly included women without additional risk factors. For twins, vaginal progesterone did not reduce preterm birth before 34 weeks (eight trials, 2046 women: RR 1·01, 95% CI 0·84-1·20) nor did 17-OHPC for twins or triplets (eight trials, 2253 women: 1·04, 0·92-1·18). Preterm premature rupture of membranes was increased with 17-OHPC exposure in multifetal gestations (rupture INTERPRETATION: Vaginal progesterone and 17-OHPC both reduced birth before 34 weeks' gestation in high-risk singleton pregnancies. Given increased underlying risk, absolute risk reduction is greater for women with a short cervix, hence treatment might be most useful for these women. Evidence for oral progesterone is insufficient to support its use. Shared decision making with woman with high-risk singleton pregnancies should discuss an individual's risk, potential benefits, harms and practicalities of intervention. Treatment of unselected multifetal pregnancies with a progestogen is not supported by the evidence.FUNDING: Patient-Centered Outcomes Research Institute.

The effectiveness and efficiency of cancer screening in real-world settings depend on many factors, including test sensitivity and specificity. Outside of select experimental studies, not everyone receives a gold standard test that can serve as a comparator in estimating screening test accuracy. Thus, many studies of screening test accuracy use the passage of time to infer whether or not cancer was present at the time of the screening test, particularly for patients with a negative screening test. We define the accuracy assessment interval as the period of time after a screening test that is used to estimate the test's accuracy. We describe how the length of this interval may bias sensitivity and specificity estimates. We call for future research to quantify bias and uncertainty in accuracy estimates and to provide guidance on setting accuracy assessment interval lengths for different cancers and screening modalities.

Overdiagnosed cancers are those that are screen-detected but never would have been symptomatic during patients' lifetimes. Indolent cancers are overdiagnosed cancers. Non-indolent cancers can be overdiagnosed when patients die of causes other than the screen-detected cancer and would have, in the absence of screening, been asymptomatic and undiagnosed at the time of death. This is termed competing cause of mortality (CCM) overdiagnosis. Deaths soon after screen detection may represent CCM overdiagnosis. We examined time from screen-detection to death among the 35 participants in the National Lung Screening Trial (NLST) low-dose computed tomography arm with screen-detected lung cancer and died of non-lung-cancer causes. Seven participants died within 6 months, and 20 died more than 24 months after diagnosis. Deaths due to non-lung cancer causes soon after screen detection were uncommon, arguing against widespread CCM overdiagnosis in the NLST. However, CCM overdiagnosis is likely more frequent in community-based screening given the higher prevalence of comorbidities.

COVID-19 has proved enormously disruptive to the provision of cancer screening, which does not just represent an initial test but an entire process, including risk detection, diagnostic follow-up, and treatment. Successful delivery of services at all points in the process has been negatively affected by the pandemic. There is a void in empirical high-quality evidence to support a specific strategy for administering cancer screening during a pandemic and its resolution phase, but several pragmatic considerations can help guide prioritization efforts. Targeting guideline-eligible people who have never been screened, or those who are significantly out of date with screening, has the potential to maximize benefits now and into the future. Disruptions to care due to the pandemic could represent an unparalleled opportunity to reassess early detection programs towards an explicit, thoughtful, and just prioritization of populations historically experiencing cancer disparities. By focusing screening services on populations that have the most to gain, and by careful and deliberate planning for the period following the pandemic, we can positively affect cancer outcomes for all.

Screening has long been portrayed as an inherently beneficial activity that saves lives, rather than as a complex mixture of potential benefits and harms that must be carefully weighed for each modality. The early success of the Pap smear in reducing deaths from cervical cancer may have inadvertently fostered simplistic messaging about unqualified benefits of screening. Over time, large-scale randomized controlled trials (RCTs) of prostate and other cancers have highlighted the potential harms caused by mass screening programs (especially those related to overdiagnosis and unnecessary treatment) and have revealed the counterintuitive elements involved in evaluating such programs. The criteria for evaluation now extend beyond the performance criteria of the test itself to include the net balance of benefits, risks, and costs. PSA screening, widely used in the United States since the late 1980s, has now been removed from the list of routinely recommended procedures, based on evidence from RCTs.

Models can be valuable tools to address uncertainty, trade-offs, and preferences when trying to understand the effects of interventions. Availability of results from two or more independently developed models that examine the same question (comparative modeling) allows systematic exploration of differences between models and the effect of these differences on model findings. Guideline groups sometimes commission comparative modeling to support their recommendation process. In this commissioned collaborative modeling, modelers work with the people who are developing a recommendation or policy not only to define the questions to be addressed but ideally, work side-by-side with each other and with systematic reviewers to standardize selected inputs and incorporate selected common assumptions. This paper describes the use of commissioned collaborative modeling by the U.S. Preventive Services Task Force (USPSTF), highlighting the general challenges and opportunities encountered and specific challenges for some topics. It delineates other approaches to use modeling to support evidence-based recommendations and the many strengths of collaborative modeling compared with other approaches. Unlike systematic reviews prepared for the USPSTF, the commissioned collaborative modeling reports used by the USPSTF in making recommendations about screening have not been required to follow a common format, sometimes making it challenging to understand key model features. This paper presents a checklist developed to critically appraise commissioned collaborative modeling reports about cancer screening topics prepared for the USPSTF.