Journal of Medical Screening

Antenatal reflex DNA screening for Down’s syndrome has a high screening performance. We aimed to determine the performance of trisomy 18 and trisomy 13 reflex DNA screening when added to Down’s syndrome screening.

In our modelled screening protocol, women provide two samples: a serum sample for a Combined test and a plasma sample for a possible DNA test. Women with Down’s syndrome, trisomy 18, or trisomy 13 Combined test risks above a single cut-off have a reflex DNA test using the plasma sample, without the need to recall them to collect another sample and provide counselling. Women with a failed DNA test (after a second attempt using a fresh plasma sample) have an Integrated test, and are classified as positive if any of the Down’s syndrome, trisomy 18, or trisomy 13 Integrated test risks are greater than 1 in 25.

At 1 in 800 term risk cut-offs for Down’s syndrome, trisomy 18, and trisomy 13, an estimated 10% of women are reflexed to DNA screening, yielding a 91% Down’s syndrome detection rate, an 89% trisomy 18 detection rate, and a 79% trisomy 13 detection rate for a 0.05% false-positive rate. At a 1 in 1900 term risk cut-off for Down’s syndrome, trisomy 18, or trisomy 13, an estimated 20% of women are reflexed to DNA screening, and this yields a 94% Down’s syndrome detection rate, a 92% trisomy 18 detection rate, and an 84% trisomy 13 detection rate for a 0.10% false-positive rate.

Reflex DNA screening for trisomies 18 and 13 can be usefully added to reflex DNA screening for Down’s syndrome.

To determine (i) if electrospray mass spectrometry–mass spectrometry with the SpOtOn Diagnostics Ltd reagent kit for sickle cell screening could be integrated into the English newborn screening programme, under routine screening conditions, and provide mass spectrometry–mass spectrometry results which match existing methods, and (ii) if common action values could be set for all manufacturers in the study, for all assessed haemoglobins, to indicate which samples require further investigation.

Anonymised residual blood spots were analysed using the SpOtOn reagent kit as per manufacturer’s instructions, in parallel with existing techniques at four laboratories. Mass spectrometry–mass spectrometry instrumentation at Laboratories A and B was AB Sciex (Warrington, UK) AP4000, and at Laboratories C and D, Waters Micromass (Manchester, UK), Xevo TQMS and Premier, respectively.

There were 23,898 results accepted from the four laboratories. Excellent specificity at 100% sensitivity was observed for haemoglobin S, haemoglobin C, haemoglobin E and haemoglobin O^Arab. A common action value was not possible for Hb C, but action values were set by manufacturer. The two haemoglobin D^Punjab cases at Laboratory D were not detected using the common action value. Conversely, false-positive results with haemoglobin D^Punjab were a problem at the remaining three laboratories.

This multicentre study demonstrates that it is possible to implement mass spectrometry–mass spectrometry into an established screening programme while maintaining consistency with existing methods for haemoglobinopathy screening. However, one of the instruments investigated cannot be recommended for use with this application.

The importance of cancer screening is well-recognized, yet there is great variation in how adherence is defined and measured. This manuscript identifies measures of screening adherence and discusses how to estimate them.

We begin by describing why screening adherence is of interest: to anticipate long-term outcomes, to understand differences in outcomes across settings, and to identify areas for improvement. We outline questions of interest related to adherence, including questions about uptake, currency or being up-to-date, and longitudinal adherence, and then identify which measures are most appropriate for each question. Our discussion of how to select measures focuses on study inclusion criteria and outcome definitions. Finally, we describe how to estimate different measures using data from two common data sources: survey studies and surveillance studies. Estimation requires consideration of data sources, inclusion criteria, and outcome definitions. Censoring often will be present and must be accounted for.

We conclude that consistent definitions and estimation of adherence to cancer screening guidelines will facilitate comparison across studies, tests, and settings, and help to elucidate areas for future research and intervention.

To assess the impact of ambient temperature on faecal immunochemical test (FIT) performance in the colorectal cancer screening programme of Emilia-Romagna (Italy).

A population-based retrospective cohort study on data from 2005 to 2011. Positive rate, detection rate, and positive predictive value rate for cancers and adenomas, and incidence rate of interval cancers after negative tests were analysed using Poisson regression models. In addition to ambient temperature, gender, age, screening history, and Local Health Unit were also considered.

In 1,521,819 tests analysed, the probability of a positive result decreased linearly with increasing temperature. Point estimates and 95% Confidence Intervals were estimated for six temperature classes (<5, 5 |−10, 10 |−15, 15 |−20, 20|−25 and ≥25℃), and referred to the 5|-10℃ class. The positive rate ratio was significantly related to temperature increase: 0.99 (0.97–1.02), 1, 0.98 (0.96–1.00), 0.96 (0.94–0.99), 0.93 (0.91–0.96), 0.92 (0.89–0.95). A linear trend was also evident for advanced adenoma detection rate ratio: 1.00 (0.96–1.04), 1, 0.98 (0.93–1.02), 0.96 (0.92–1.00), 0.92 (0.88–0.96), 0.94 (0.88–1.01). The effect was less linear, but still important, for cancer detection rates: 0.95 (0.85–1.06), 1, 1.00 (0.90–1.10), 0.94 (0.85–1.05), 0.81 (0.72–0.92), 0.93 (0.80–1.09). No association or linear trend was found for positive predictive values or risk of interval cancer, despite an excess of +16% in the highest temperature class for interval cancer.

Ambient temperatures can affect screening performance. Continued monitoring is needed to verify the effect of introducing FIT tubes with a new buffer, which should guarantee a higher stability of haemoglobin.

Estimating overdiagnosis in cancer screening is complicated. Using observational data, estimation of the expected incidence in the screening period and taking account of lead time are two major problems.

Using data from the Cancer Registry of Norway and the Norwegian Breast Cancer Screening Programme, we estimated incidence trends, using age-specific trends by year in the pre-screening period (1985–95). We also estimated sojourn time and sensitivity using interval cancers only. Thus, lead time estimates were uncontaminated by overdiagnosed cases. Finally, we derived estimates of overdiagnosis separately for all cancers, and for invasive cancers only, correcting for lead time, using two different methods.

Our results indicate that overdiagnosis of all cancers, invasive and in situ, constituted 15–17% of all screen-detected cancers in 1996–2009. For invasive cancers only, the corresponding figures were -2 to 7% in the same period, suggesting that a substantial proportion of the overdiagnosis in the Norwegian Programme was due to ductal carcinoma in situ.

Using short-term trends, instead of long, prior to screening was more effective in predicting incidence in the screening epoch. In addition, sojourn time estimation using symptomatic cancers only avoids over-correction for lead time and consequently underestimation of overdiagnosis. Longer follow-up will provide more precise estimates of overdiagnosis.

To compute a ratio between the estimated numbers of lives saved from breast cancer death and the number of women diagnosed with a breast cancer that never would have been diagnosed during the woman’s lifetime had she not attended screening (epidemiologic over-diagnosis) in the Norwegian Breast Cancer Screening Program.

The Norwegian Breast Cancer Screening Program invites women aged 50–69 to biennial mammographic screening. Results from published studies using individual level data from the programme for estimating breast cancer mortality and epidemiologic over-diagnosis comprised the basis for the ratio. The mortality reduction varied from 36.8% to 43% among screened women, while estimates on epidemiologic over-diagnosis ranged from 7% to 19.6%. We computed the average estimates for both values. The benefit–detriment ratio, number of lives saved, and number of women over-diagnosed were computed for different scenarios of reduction in breast cancer mortality and epidemiologic over-diagnosis.

For every 10,000 biennially screened women, followed until age 79, we estimated that 53–61 (average 57) women were saved from breast cancer death, and 45–126 (average 82) were over-diagnosed. The benefit–detriment ratio using average estimates was 1:1.4, indicating that the programme saved about one life per 1–2 women with epidemiologic over-diagnosis.

The benefit–detriment ratio estimates of the Norwegian Breast Cancer Screening Program, expressed as lives saved from breast cancer death and epidemiologic over-diagnosis, should be interpreted with care due to substantial uncertainties in the estimates, and the differences in the scale of values of the events compared.

Although early detection of cancer through screening can prevent cancer deaths, a drawback of screening is overdiagnosis. Overdiagnosis has been much debated in breast cancer screening, but less so in cervical cancer screening. We examined the impact of overdiagnosis by comparing two screening programmes in the Netherlands.

We estimated overdiagnosis rates by microsimulation for breast cancer screening and cervical cancer screening, using a cohort of women born in 1982 with lifelong follow-up. Overdiagnosis estimates were made analogous to two definitions formed by the UK 2012 breast screening review. Pre-invasive disease was included in both definitions.

Screening prevented 921 cervical cancers (−55%) and 378 cervical cancer deaths (−59%), and 169 (−1.3%) breast cancer cases and 970 breast cancer deaths (−21%). The cervical cancer overdiagnosis rate was 74.8% (including pre-invasive disease). Breast cancer overdiagnosis was estimated at 2.5% (including pre-invasive disease). For women of all ages in breast cancer screening, an excess of 207 diagnoses/100,000 women was found, compared with an excess of 3999 diagnoses/100,000 women in cervical cancer screening.

For breast cancer, the frequency of overdiagnosis in screening is relatively low, but consequences are evident. For cervical cancer, the frequency of overdiagnosis in screening is high, because of detection of pre-invasive disease, but the consequences per case are relatively small due to less invasive treatment. This illustrates that it is necessary to present overdiagnosis in relation to disease stage and consequences.

Comprehensive nationwide monitoring and evaluation of screening through registry-based review of key indicators is necessary for programme optimization, especially as new tests and strategies are introduced. We aimed to investigate and report on the use of these key indicators in the Swedish programme.

Organized population-based cervical screening targeting women aged 23–50 and 51–60 every three and five years, respectively, is regionally implemented in Sweden. All cytological and histopathological test results and invitations are exported to the National Cervical Screening Registry. We describe the methods to obtain registry-based quality indicators by age, region, and calendar period.

In 2013, there were 633,592 cervical smears in Sweden, of which 69% were organized smears resulting from an invitation. Screening test coverage for women aged 23–60 was 80% and similar for the previous decade, but varied greatly between and within counties over-time. Among women aged 23–25, test coverage increased dramatically during the previous six years, reaching 87% in 2013. The proportion of women with cytological high-grade cervical lesions found in cytology that had been followed-up with biopsy within one year was 97%. Major variations in cervical cancer incidence between counties were observed.

Registry-based analyses of key quality indicators provided the basis for prioritizing improvements of the organized cervical screening programme.