| 1. |
- Baldeh, Tejan, et al.
(författare)
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Development and use of health outcome descriptors : a guideline development case study
- 2020
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Ingår i: Health and Quality of Life Outcomes. - : BioMed Central. - 1477-7525 .- 1477-7525. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: During healthcare guideline development, panel members often have implicit, different definitions of health outcomes that can lead to misunderstandings about how important these outcomes are and how to balance benefits and harms. McMaster GRADE Centre researchers developed ‘health outcome descriptors’ for standardizing descriptions of health outcomes and overcoming these problems to support the European Commission Initiative on Breast Cancer (ECIBC) Guideline Development Group (GDG). We aimed to determine which aspects of the development, content, and use of health outcome descriptors were valuable to guideline developers.Methods: We developed 24 health outcome descriptors related to breast cancer screening and diagnosis for the European Commission Breast Guideline Development Group (GDG). Eighteen GDG members provided feedback in written format or in interviews. We then evaluated the process and conducted two health utility rating surveys.Results: Feedback from GDG members revealed that health outcome descriptors are probably useful for developing recommendations and improving transparency of guideline methods. Time commitment, methodology training, and need for multidisciplinary expertise throughout development were considered important determinants of the process. Comparison of the two health utility surveys showed a decrease in standard deviation in the second survey across 21 (88%) of the outcomes.Conclusions: Health outcome descriptors are feasible and should be developed prior to the outcome prioritization step in the guideline development process. Guideline developers should involve a subgroup of multidisciplinary experts in all stages of development and ensure all guideline panel members are trained in guideline methodology that includes understanding the importance of defining and understanding the outcomes of interest.
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| 2. |
- Boita, Joana, et al.
(författare)
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Development and content validity evaluation of a candidate instrument to assess image quality in digital mammography : A mixed-method study
- 2021
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Ingår i: European Journal of Radiology. - : Elsevier BV. - 0720-048X. ; 134
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To develop a candidate instrument to assess image quality in digital mammography, by identifying clinically relevant features in images that are affected by lower image quality. Methods: Interviews with fifteen expert breast radiologists from five countries were conducted and analysed by using adapted directed content analysis. During these interviews, 45 mammographic cases, containing 44 lesions (30 cancers, 14 benign findings), and 5 normal cases, were shown with varying image quality. The interviews were performed to identify the structures from breast tissue and lesions relevant for image interpretation, and to investigate how image quality affected the visibility of those structures. The interview findings were used to develop tentative items, which were evaluated in terms of wording, understandability, and ambiguity with expert breast radiologists. The relevance of the tentative items was evaluated using the content validity index (CVI) and modified kappa index (k*). Results: Twelve content areas, representing the content of image quality in digital mammography, emerged from the interviews and were converted into 29 tentative items. Fourteen of these items demonstrated excellent CVI ≥ 0.78 (k* > 0.74), one showed good CVI < 0.78 (0.60 ≤ k* ≤ 0.74), while fourteen were of fair or poor CVI < 0.78 (k* ≤ 0.59). In total, nine items were deleted and five were revised or combined resulting in 18 items. Conclusions: By following a mixed-method methodology, a candidate instrument was developed that may be used to characterise the clinically-relevant impact that image quality variations can have on digital mammography.
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| 3. |
- Boita, Joana, et al.
(författare)
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How does image quality affect radiologists’ perceived ability for image interpretation and lesion detection in digital mammography?
- 2021
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Ingår i: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 31:7, s. 5335-5343
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: To study how radiologists’ perceived ability to interpret digital mammography (DM) images is affected by decreases in image quality. Methods: One view from 45 DM cases (including 30 cancers) was degraded to six levels each of two acquisition-related issues (lower spatial resolution and increased quantum noise) and three post-processing-related issues (lower and higher contrast and increased correlated noise) seen during clinical evaluation of DM systems. The images were shown to fifteen breast screening radiologists from five countries. Aware of lesion location, the radiologists selected the most-degraded mammogram (indexed from 1 (reference) to 7 (most degraded)) they still felt was acceptable for interpretation. The median selected index, per degradation type, was calculated separately for calcification and soft tissue (including normal) cases. Using the two-sided, non-parametric Mann-Whitney test, the median indices for each case and degradation type were compared. Results: Radiologists were not tolerant to increases (medians: 1.5 (calcifications) and 2 (soft tissue)) or decreases (median: 2, for both types) in contrast, but were more tolerant to correlated noise (median: 3, for both types). Increases in quantum noise were tolerated more for calcifications than for soft tissue cases (medians: 3 vs. 4, p = 0.02). Spatial resolution losses were considered less acceptable for calcification detection than for soft tissue cases (medians: 3.5 vs. 5, p = 0.001). Conclusions: Perceived ability of radiologists for image interpretation in DM was affected not only by image acquisition-related issues but also by image post-processing issues, and some of those issues affected calcification cases more than soft tissue cases. Key Points: • Lower spatial resolution and increased quantum noise affected the radiologists’ perceived ability to interpret calcification cases more than soft tissue lesion or normal cases. • Post-acquisition image processing-related effects, not only image acquisition-related effects, also impact the perceived ability of radiologists to interpret images and detect lesions. • In addition to current practices, post-acquisition image processing-related effects need to also be considered during the testing and evaluation of digital mammography systems.
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| 4. |
- Boita, Joana, et al.
(författare)
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Validation of a candidate instrument to assess image quality in digital mammography using ROC analysis
- 2021
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Ingår i: European Journal of Radiology. - : Elsevier BV. - 1872-7727 .- 0720-048X. ; 139
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Tidskriftsartikel (refereegranskat)abstract
- PurposeTo validate a candidate instrument, to be used by different professionals to assess image quality in digital mammography (DM), against detection performance results.MethodsA receiver operating characteristics (ROC) study was conducted to assess the detection performance in DM images with four different image quality levels due to different quality issues. Fourteen expert breast radiologists from five countries assessed a set of 80 DM cases, containing 60 lesions (40 cancers, 20 benign findings) and 20 normal cases. A visual grading analysis (VGA) study using a previously-described candidate instrument was conducted to evaluate a subset of 25 of the images used in the ROC study. Eight radiologists that had participated in the ROC study, and seven expert breast-imaging physicists, evaluated this subset. The VGA score (VGAS) and the ROC and visual grading characteristics (VGC) areas under the curve (AUCROC and AUCVGC) were compared.ResultsNo large differences in image quality among the four levels were detected by either ROC or VGA studies. However, the ranking of the four levels was consistent: level 1 (partial AUCROC: 0.070, VGAS: 6.77) performed better than levels 2 (0.066, 6.15), 3 (0.061, 5.82), and 4 (0.062, 5.37). Similarity between radiologists’ and physicists’ assessments was found (average VGAS difference of 10 %).ConclusionsThe results from the candidate instrument were found to correlate with those from ROC analysis, when used by either observer group. Therefore, it may be used by different professionals, such as radiologists, radiographers, and physicists, to assess clinically-relevant image quality variations in DM.
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| 5. |
- Broeders, Mireille, et al.
(författare)
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The impact of mammographic screening on breast cancer mortality in Europe : a review of observational studies
- 2012
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Ingår i: Journal of Medical Screening. - : SAGE Publications. - 0969-1413 .- 1475-5793. ; 19, s. 14-25
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Tidskriftsartikel (refereegranskat)abstract
- Objectives To assess the impact of population-based mammographic screening on breast cancer mortality in Europe, considering different methodologies and limitations of the data. Methods We conducted a systematic literature review of European trend studies (n = 17), incidence-based mortality (IBM) studies (n = 20) and case-control (CC) studies (n = 8). Estimates of the reduction in breast cancer mortality for women invited versus not invited and/or for women screened versus not screened were obtained. The results of IBM studies and CC studies were each pooled using a random effects meta-analysis. Results Twelve of the 17 trend studies quantified the impact of population-based screening on breast cancer mortality. The estimated breast cancer mortality reductions ranged from 1% to 9% per year in studies reporting an annual percentage change, and from 28% to 36% in those comparing post- and prescreening periods. In the IBM studies, the pooled mortality reduction was 25% (relative risk [RR] 0.75, 95% confidence interval [CI] 0.69-0.81) among invited women and 38% (RR 0.62, 95% CI 0.56-0.69) among those actually screened. The corresponding pooled estimates from the CC studies were 31% (odds ratio [OR] 0.69, 95% CI 0.57-0.83), and 48% (OR 0.52, 95% CI 0.42-0.65) adjusted for self-selection. Conclusions Valid observational designs are those where sufficient longitudinal individual data are available, directly linking a woman's screening history to her cause of death. From such studies, the best 'European' estimate of breast cancer mortality reduction is 25-31% for women invited for screening, and 38-48% for women actually screened. Much of the current controversy on breast cancer screening is due to the use of inappropriate methodological approaches that are unable to capture the true effect of mammographic screening.
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| 6. |
- Giorgi Rossi, Paolo, et al.
(författare)
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Recommendations from the European Commission Initiative on Breast Cancer for multigene testing to guide the use of adjuvant chemotherapy in patients with early breast cancer, hormone receptor positive, HER-2 negative
- 2021
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Ingår i: British Journal of Cancer. - : Springer. - 0007-0920 .- 1532-1827. ; 124:9, s. 1503-1512
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Forskningsöversikt (refereegranskat)abstract
- Background: Predicting the risk of recurrence and response to chemotherapy in women with early breast cancer is crucial to optimise adjuvant treatment. Despite the common practice of using multigene tests to predict recurrence, existing recommendations are inconsistent. Our aim was to formulate healthcare recommendations for the question “Should multigene tests be used in women who have early invasive breast cancer, hormone receptor-positive, HER2-negative, to guide the use of adjuvant chemotherapy?”Methods: The European Commission Initiative on Breast Cancer (ECIBC) Guidelines Development Group (GDG), a multidisciplinary guideline panel including experts and three patients, developed recommendations informed by systematic reviews of the evidence. Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision frameworks were used. Four multigene tests were evaluated: the 21-gene recurrence score (21-RS), the 70-gene signature (70-GS), the PAM50 risk of recurrence score (PAM50-RORS), and the 12-gene molecular score (12-MS).Results: Five studies (2 marker-based design RCTs, two treatment interaction design RCTs and 1 pooled individual data analysis from observational studies) were included; no eligible studies on PAM50-RORS or 12-MS were identified and the GDG did not formulate recommendations for these tests.Conclusions: The ECIBC GDG suggests the use of the 21-RS for lymph node-negative women (conditional recommendation, very low certainty of evidence), recognising that benefits are probably larger in women at high risk of recurrence based on clinical characteristics. The ECIBC GDG suggests the use of the 70-GS for women at high clinical risk (conditional recommendation, low certainty of evidence), and recommends not using 70-GS in women at low clinical risk (strong recommendation, low certainty of evidence).
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| 7. |
- Muratov, Sergei, et al.
(författare)
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Monitoring and evaluation of breast cancer screening programmes : selecting candidate performance indicators
- 2020
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Ingår i: BMC Cancer. - : BioMed Central. - 1471-2407 .- 1471-2407. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: In the scope of the European Commission Initiative on Breast Cancer (ECIBC) the Monitoring and Evaluation (M&E) subgroup was tasked to identify breast cancer screening programme (BCSP) performance indicators, including their acceptable and desirable levels, which are associated with breast cancer (BC) mortality. This paper documents the methodology used for the indicator selection.Methods: The indicators were identified through a multi-stage process. First, a scoping review was conducted to identify existing performance indicators. Second, building on existing frameworks for making well-informed health care choices, a specific conceptual framework was developed to guide the indicator selection. Third, two group exercises including a rating and ranking survey were conducted for indicator selection using pre-determined criteria, such as: relevance, measurability, accurateness, ethics and understandability. The selected indicators were mapped onto a BC screening pathway developed by the M&E subgroup to illustrate the steps of BC screening common to all EU countries.Results: A total of 96 indicators were identified from an initial list of 1325 indicators. After removing redundant and irrelevant indicators and adding those missing, 39 candidate indicators underwent the rating and ranking exercise. Based on the results, the M&E subgroup selected 13 indicators: screening coverage, participation rate, recall rate, breast cancer detection rate, invasive breast cancer detection rate, cancers >20mm, cancers <= 10mm, lymph node status, interval cancer rate, episode sensitivity, time interval between screening and first treatment, benign open surgical biopsy rate, and mastectomy rate.Conclusion: This systematic approach led to the identification of 13 BCSP candidate performance indicators to be further evaluated for their association with BC mortality.
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| 8. |
- Njor, Sisse, et al.
(författare)
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Breast cancer mortality in mammographic screening in Europe : a review of incidence-based mortality studies
- 2012
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Ingår i: Journal of Medical Screening. - : SAGE Publications. - 0969-1413 .- 1475-5793. ; 19, s. 33-41
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Forskningsöversikt (refereegranskat)abstract
- Objectives To estimate the impact of service mammography screening on breast cancer mortality using European incidence-based mortality (IBM) studies (or refined mortality studies). IBM studies include only breast cancer deaths occurring in women with breast cancer diagnosed after their first invitation to screening. Methods We conducted a literature review and identified 20 publications based on IBM studies. They were classified according to the method used for estimating the expected breast cancer mortality in the absence of screening: (1) women not yet invited; (2) historical data from the same region as well as from historical and current data from a region without screening; and (3) historical comparison group combined with data for non-participants. Results The estimated effect of mammography screening on breast cancer mortality varied across studies. The relative risks were 0.76-0.81 in group 1; 0.75-0.90 in group 2; and 0.52-0.89 in group 3. Study databases overlapped in both Swedish and Finnish studies, adjustment for lead time was not optimal in all studies, and some studies had other methodological limitations. There was less variability in the relative risks after allowing for the methodological shortcomings. Conclusions Based on evidence from the most methodologically sound IBM studies, the most likely impact of European service mammography screening programmes was a breast cancer mortality reduction of 26% (95% confidence interval 13-36%) among women invited for screening and followed up for 6-11 years.
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| 9. |
- Rodriguez-Ruiz, Alejandro, et al.
(författare)
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Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study
- 2019
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Ingår i: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 29:9, s. 4825-4832
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To study the feasibility of automatically identifying normal digital mammography (DM) exams with artificial intelligence (AI) to reduce the breast cancer screening reading workload. Methods and materials: A total of 2652 DM exams (653 cancer) and interpretations by 101 radiologists were gathered from nine previously performed multi-reader multi-case receiver operating characteristic (MRMC ROC) studies. An AI system was used to obtain a score between 1 and 10 for each exam, representing the likelihood of cancer present. Using all AI scores between 1 and 9 as possible thresholds, the exams were divided into groups of low- and high likelihood of cancer present. It was assumed that, under the pre-selection scenario, only the high-likelihood group would be read by radiologists, while all low-likelihood exams would be reported as normal. The area under the reader-averaged ROC curve (AUC) was calculated for the original evaluations and for the pre-selection scenarios and compared using a non-inferiority hypothesis. Results: Setting the low/high-likelihood threshold at an AI score of 5 (high likelihood > 5) results in a trade-off of approximately halving (− 47%) the workload to be read by radiologists while excluding 7% of true-positive exams. Using an AI score of 2 as threshold yields a workload reduction of 17% while only excluding 1% of true-positive exams. Pre-selection did not change the average AUC of radiologists (inferior 95% CI > − 0.05) for any threshold except at the extreme AI score of 9. Conclusion: It is possible to automatically pre-select exams using AI to significantly reduce the breast cancer screening reading workload. Key Points: • There is potential to use artificial intelligence to automatically reduce the breast cancer screening reading workload by excluding exams with a low likelihood of cancer. • The exclusion of exams with the lowest likelihood of cancer in screening might not change radiologists’ breast cancer detection performance. • When excluding exams with the lowest likelihood of cancer, the decrease in true-positive recalls would be balanced by a simultaneous reduction in false-positive recalls.
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| 10. |
- Rodriguez-Ruiz, Alejandro, et al.
(författare)
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Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography : Comparison With 101 Radiologists
- 2019
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 1460-2105 .- 0027-8874. ; 111:9, s. 916-922
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Artificial intelligence (AI) systems performing at radiologist-like levels in the evaluation of digital mammography (DM) would improve breast cancer screening accuracy and efficiency. We aimed to compare the stand-alone performance of an AI system to that of radiologists in detecting breast cancer in DM.METHODS: Nine multi-reader, multi-case study datasets previously used for different research purposes in seven countries were collected. Each dataset consisted of DM exams acquired with systems from four different vendors, multiple radiologists' assessments per exam, and ground truth verified by histopathological analysis or follow-up, yielding a total of 2652 exams (653 malignant) and interpretations by 101 radiologists (28 296 independent interpretations). An AI system analyzed these exams yielding a level of suspicion of cancer present between 1 and 10. The detection performance between the radiologists and the AI system was compared using a noninferiority null hypothesis at a margin of 0.05.RESULTS: The performance of the AI system was statistically noninferior to that of the average of the 101 radiologists. The AI system had a 0.840 (95% confidence interval [CI] = 0.820 to 0.860) area under the ROC curve and the average of the radiologists was 0.814 (95% CI = 0.787 to 0.841) (difference 95% CI = -0.003 to 0.055). The AI system had an AUC higher than 61.4% of the radiologists.CONCLUSIONS: The evaluated AI system achieved a cancer detection accuracy comparable to an average breast radiologist in this retrospective setting. Although promising, the performance and impact of such a system in a screening setting needs further investigation.
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