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Objective: To investigate the effect of interpregnancy interval (IPI) on preterm birth (PTB) according to whether the previous birth was preterm or term. Design: Cohort study. Setting: USA (California), Australia, Finland, Norway (1980–2017). Population: Women who gave birth to first and second (n = 3 213 855) singleton livebirths. Methods: Odds ratios (ORs) for PTB according to IPIs were modelled using logistic regression with prognostic score stratification for potential confounders. Within‐site ORs were pooled by random effects meta‐analysis. Outcome measure: PTB (gestational age <37 weeks). Results: Absolute risk of PTB for each IPI was 3–6% after a previous term birth and 17–22% after previous PTB. ORs for PTB differed between previous term and preterm births in all countries (P‐for‐interaction ≤ 0.001). For women with a previous term birth, pooled ORs were increased for IPI <6 months (OR 1.50, 95% CI 1.43–1.58); 6–11 months (OR 1.10, 95% CI 1.04–1.16); 24–59 months (OR 1.16, 95% CI 1.13–1.18); and ≥ 60 months (OR 1.72, 95%CI 1.60–1.86), compared with 18–23 months. For previous PTB, ORs were increased for <6 months (OR 1.30, 95% CI 1.18–1.42) and ≥60 months (OR 1.29, 95% CI 1.17–1.42), but were less than ORs among women with a previous term birth (P < 0.05). Conclusions: Associations between IPI and PTB are modified by whether or not the previous pregnancy was preterm. ORs for short and long IPIs were higher among women with a previous term birth than a previous PTB, which for short IPI is consistent with the maternal depletion hypothesis. Given the high risk of recurrence and assuming a causal association between IPI and PTB, IPI remains a potentially modifiable risk factor for women with previous PTB. Short versus long interpregnancy intervals associated with higher ORs for preterm birth (PTB) after a previous PTB. Short versus long interpregnancy intervals associated with higher ORs for preterm birth (PTB) after a previous PTB. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to synthesise evidence from prospective studies of digital breast tomosynthesis (DBT) screening to assess its effectiveness compared to digital mammography (DM). Specifically, we examined whether DBT reduces interval cancer rates (ICRs) in population breast cancer screening., Materials and Methods: We performed a systematic review and meta-analysis of DBT screening studies (identified from January 2013 to March 2024). We included both RCTs and non-randomised prospective studies that used an independent comparison for our primary outcome ICRs. The risk of bias was assessed with QUADAS-2. We compared the ICR, cancer detection rate (CDR), and recall rate of DBT and DM screening using random effects meta-analysis models. Subgroup analyses estimated outcomes by study design. Sensitivity analyses estimated absolute effects from relative effects., Results: Ten prospective studies (three RCTs, seven non-randomised) were eligible; all had a low risk of bias. There were 205,245 DBT-screened and 306,476 DM-screened participants with follow-up for interval cancer data. The pooled absolute ICR did not significantly differ between DBT and DM: -2.92 per 10,000 screens (95% CI: -6.39 to 0.54); however subsequent subgroup analysis indicated certain study designs may have biased this ICR estimate. Pooled ICR from studies that only sampled groups from the same time and region indicated DBT led to 5.50 less IC per 10,000 screens (95% CI: -9.47 to -1.54). Estimates from subgroup analysis that compared randomised and non-randomised trials did not significantly differ., Conclusion: This meta-analysis provides suggestive evidence that DBT decreases ICR relative to DM screening; further evidence is needed to reduce uncertainty regarding ICR differences between DBT and DM., Key Points: Question Does DBT have long-term benefits over standard DM? Finding We find suggestive evidence in our primary analysis and stronger evidence in a follow-up analysis that DBT reduces interval cancers. Clinical relevance This meta-analysis provides the first indication that DBT may detect additional cancers that are clinically meaningful, based on suggestive evidence of a reduction in ICR. This finding does not preclude the simultaneous possibility of overdiagnosis., (© 2024. The Author(s).)

As breast screening services move towards use of healthcare AI (HCAI) for screen reading, research on public views of HCAI can inform more person-centered implementation. We synthesise reviews of public views of HCAI in general, and review primary studies of women's views of AI in breast screening. People generally appear open to HCAI and its potential benefits, despite a wide range of concerns; similarly, women are open towards AI in breast screening because of the potential benefits, but are concerned about a wide range of risks. Women want radiologists to remain central; oversight, evaluation and performance, care, equity and bias, transparency, and accountability are key issues; women may be less tolerant of AI error than of human error. Using our recent Australian primary study, we illustrate both the value of informing participants before collecting data, and women's views. The 40 screening-age women in this study stipulated four main conditions on breast screening AI implementation: 1) maintaining human control; 2) strong evidence of performance; 3) supporting familiarisation with AI; and 4) providing adequate reasons for introducing AI. Three solutions were offered to support familiarisation: transparency and information; slow and staged implementation; and allowing women to opt-out of AI reading. We provide recommendations to guide both implementation of AI in healthcare and research on public views of HCAI. Breast screening services should be transparent about AI use and share information about breast screening AI with women. Implementation should be slow and staged, providing opt-out options if possible. Screening services should demonstrate strong governance to maintain clinician control, demonstrate excellent AI system performance, assure data protection and bias mitigation, and give good reasons to justify implementation. When these measures are put in place, women are more likely to see HCAI use in breast screening as legitimate and acceptable., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: There is limited evidence on the performance of digital breast tomosynthesis (DBT) in populations at increased risk of breast cancer. Our objective was to systematically review evidence on the performance of DBT versus digital mammography (DM) in women with a family history of breast cancer (FHBC)., Methods: We searched 5 databases (2011-January 2024) for studies comparing DBT and DM in women with a FHBC that reported any measure of cancer detection, recall, sensitivity and specificity. Findings were presented using a descriptive and narrative approach. Risk of bias was assessed using QUADAS-2/C., Results: Five (4 screening, 1 diagnostic) studies were included (total 3089 DBT, 3024 DM) with most (4/5) being prospective including 1 RCT. All studies were assessed as being at high risk of bias or applicability concern. Four screening studies reported recall rate (range: DBT: 2.7%-4.5%, DM: 2.8%-11.5%) with 3 reporting DBT had lower rates than DM. Cancer detection rates (CDR) were reported in the same studies (DBT: 5.1-11.6 per 1000, DM: 3.8-8.3); 3 reported higher CDR for DBT (vs. DM), and 1 reported same CDR for both. Compared with DM, higher values for sensitivity, specificity and PPV for DBT were reported in 2 studies., Conclusion: This review provides early evidence that DBT may outperform DM for screening women with a FHBC. Our findings support further evaluation of DBT in this population. However, summarized findings were based on few studies and participants, and high-quality studies with improved methodology are needed to address biases identified in our review., Competing Interests: Disclosure JML discloses that her spouse is CEO and shareholder of a privately held medical diagnostics company (Day Zero Diagnostics) that has no imaging component or oncology focus., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Biopsy-proven breast lesions such as atypical ductal hyperplasia (ADH) or atypical lobular hyperplasia (ALH), lobular carcinoma in situ (LCIS) and flat epithelial atypia (FEA) increase subsequent risk of breast cancer (BC), but long-term risk has not been synthesized. A systematic review was conducted to quantify future risk of breast cancer accounting for time since diagnosis of these high-risk lesions., Methods: A systematic search of literature from 2000 was performed to identify studies reporting BC as an outcome following core-needle or excision biopsy histology diagnosis of ADH, ALH, LCIS, lobular neoplasia (LN) or FEA. Meta-analyses were conducted to estimate cumulative BC incidence at five-yearly intervals following initial diagnosis for each histology type., Results: Seventy studies reporting on 47,671 subjects met eligibility criteria. BC incidence at five years post-diagnosis with a high-risk lesion was estimated to be 9.3 % (95 % CI 6.9-12.5 %) for LCIS, 6.6 % (95 % CI 4.4-9.7 %) for ADH, 9.7 % (95 % CI 5.3-17.2 %) for ALH, 8.6 % (95 % CI 6.5-11.4 %) for LN, and 3.8 % (95 % CI 1.2-11.7 %) for FEA. At ten years post-diagnosis, BC incidence was estimated to be 11.8 % (95 % CI 9.0-15.3 %) for LCIS, 13.9 % (95 % CI 7.8-23.6 %) for ADH, 15.4 % (95 % CI 7.2-29.3 %) for ALH, 17.0 % (95 % CI 7.2-35.3 %) for LN and 7.2 % (95 % CI 2.2-21.2 %) for FEA., Conclusion: Our findings demonstrate increased BC risk sustained over time since initial diagnosis of high-risk breast lesions, varying by lesion type, with relatively less evidence for FEA., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to declare., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

This study aimed to estimate participation in private breast screening in Queensland, Australia, where public-funded screening is implemented, and to identify factors associated with the screening setting, using an online survey (999 female respondents aged 40-74). Screening-specific and socio-demographic factors were collected. Multivariable logistic regression was used to identify factors associated with screening setting (public vs private) and screening recency (<2 vs ≥2 years). Participation estimates were 53.2% (95% confidence interval, CI: 50.0%-56.3%) and 10.9% (9.0%-13.0%) for national screening program and private screening, respectively. In the screening setting model, participation in private screening was significantly associated with longer time since last screening (>4 versus <2 years, odds ratio (OR) = 7.3, 95%CI: 4.1-12.9, p  < 0.001), having symptoms (OR = 9.5, 5.8-15.5, p  < 0.001), younger age (40-49 versus 50-74 years, OR = 1.8, 1.1-3.0, p  = 0.018) and having children <18 years in household (OR = 2.4, 1.5-3.9, p  < 0.001). In the screening recency model, only screening setting was statistically significant and private screening was associated with screening recency ≥2 years (OR = 4.0, 2.8-5.7, p  < 0.001). Around one in nine women screen outside of the BreastScreen Queensland program. Clinical and socio-demographic factors associated with participation in private screening were identified, providing knowledge relevant to the program's endeavours to improve screening participation., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Purpose: Artificial intelligence (AI) for reading breast screening mammograms could potentially replace (some) human-reading and improve screening effectiveness. This systematic review aims to identify and quantify the types of AI errors to better understand the consequences of implementing this technology., Methods: Electronic databases were searched for external validation studies of the accuracy of AI algorithms in real-world screening mammograms. Descriptive synthesis was performed on error types and frequency. False negative proportions (FNP) and false positive proportions (FPP) were pooled within AI positivity thresholds using random-effects meta-analysis., Results: Seven retrospective studies (447,676 examinations; published 2019-2022) met inclusion criteria. Five studies reported AI error as false negatives or false positives. Pooled FPP decreased incrementally with increasing positivity threshold (71.83% [95% CI 69.67, 73.90] at Transpara 3 to 10.77% [95% CI 8.34, 13.79] at Transpara 9). Pooled FNP increased incrementally from 0.02% [95% CI 0.01, 0.03] (Transpara 3) to 0.12% [95% CI 0.06, 0.26] (Transpara 9), consistent with a trade-off with FPP. Heterogeneity within thresholds reflected algorithm version and completeness of the reference standard. Other forms of AI error were reported rarely (location error and technical error in one study each)., Conclusion: AI errors are largely interpreted in the framework of test accuracy. FP and FN errors show expected variability not only by positivity threshold, but also by algorithm version and study quality. Reporting of other forms of AI errors is sparse, despite their potential implications for adoption of the technology. Considering broader types of AI error would add nuance to reporting that can inform inferences about AI's utility., (© 2024. The Author(s).)

Objectives: Film mammography has been replaced by digital mammography in breast screening programs globally. This led to a small increase in the rate of detection, but whether the detection of clinically important cancers increased is uncertain. We aimed to assess the impact on tumor characteristics of screen-detected and interval breast cancers., Study Design and Setting: We searched seven databases from inception to October 08, 2023, for publications comparing film and digital mammography within the same population of asymptomatic women at population (average) risk of breast cancer. We recorded reported tumor characteristics and assessed risk of bias using the Risk Of Bias In Non-randomised Studies - of Interventions tool. We synthesized results using meta-analyses of random effects., Results: Eighteen studies were included in the analysis from 8 countries, including 11,592,225 screening examinations (8,117,781 film; 3,474,444 digital). There were no differences in tumor size, morphology, grade, node status, receptor status, or stage in the pooled differences for screen-detected and interval invasive cancer tumor characteristics. There were statistically significant increases in screen-detected ductal carcinoma in situ (DCIS) across all grades: 0.05 (0.00-0.11), 0.14 (0.05-0.22), and 0.19 (0.05-0.33) per 1000 screens for low, intermediate, and high-grade DCIS, respectively. There were similar (non-statistically significant) increases in screen-detected invasive cancer across all grades., Conclusion: The increased detection of all grades of DCIS and invasive cancer may indicate both increased early detection of more aggressive disease and increased overdiagnosis., Competing Interests: Declaration of competing interest None declared., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Digital breast tomosynthesis (DBT) for breast cancer screening has been shown in international trials to increase cancer detection compared with mammography; however, results have varied across screening settings, and currently there is limited and conflicting evidence on interval cancer rates (a surrogate for screening effectiveness). Australian pilot data also indicated substantially longer screen-reading time for DBT posing a barrier for adoption. There is a critical need for evidence on DBT to inform its role in Australia, including evaluation of potentially more feasible models of implementation, and quantification of screening outcomes by breast density which has global relevance., Methods: This study is a prospective trial embedded in population-based Australian screening services (Maroondah BreastScreen, Eastern Health, Victoria) comparing hybrid screening comprising DBT (mediolateral oblique view) and digital mammography (cranio-caudal view) with standard mammography screening in a concurrent group attending another screening site. All eligible women aged ≥40 years attending the Maroondah service for routine screening will be enrolled (unless they do not provide verbal consent and opt-out of hybrid screening; are unable to provide consent; or where a 'pushback' image on hybrid DBT cannot be obtained). Each arm will enrol 20,000 women. The primary outcomes are cancer detection rate (per 1000 screens) and recall rate (percentage). Secondary outcomes include 'opt-out' rate; cohort characteristics; cancer characteristics; assessment outcomes; screen-reading time; and interval cancer rate at 24-month follow-up. Automated volumetric breast density will be measured to allow stratification of outcomes by mammographic density. Stratification by age and screening round will also be undertaken. An interim analysis will be undertaken after the first 5000 screens in the intervention group., Discussion: This is the first Australian prospective trial comparing hybrid DBT/mammography with standard mammography screening that is powered to show differences in cancer detection. Findings will inform future implementation of DBT in screening programs world-wide and provide evidence on whether DBT should be adopted in the broader BreastScreen program in Australia or in subgroups of screening participants., Trial Registration: The trial is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR, ACTRN12623001144606, https://www.anzctr.org.au/). Registration will be updated to reflect trial progress and protocol amendments., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: To summarize the literature regarding the performance of mammography-image based artificial intelligence (AI) algorithms, with and without additional clinical data, for future breast cancer risk prediction., Materials and Methods: A systematic literature review was performed using six databases (medRixiv, bioRxiv, Embase, Engineer Village, IEEE Xplore, and PubMed) from 2012 through September 30, 2022. Studies were included if they used real-world screening mammography examinations to validate AI algorithms for future risk prediction based on images alone or in combination with clinical risk factors. The quality of studies was assessed, and predictive accuracy was recorded as the area under the receiver operating characteristic curve (AUC)., Results: Sixteen studies met inclusion and exclusion criteria, of which 14 studies provided AUC values. The median AUC performance of AI image-only models was 0.72 (range 0.62-0.90) compared with 0.61 for breast density or clinical risk factor-based tools (range 0.54-0.69). Of the seven studies that compared AI image-only performance directly to combined image + clinical risk factor performance, six demonstrated no significant improvement, and one study demonstrated increased improvement., Conclusions: Early efforts for predicting future breast cancer risk based on mammography images alone demonstrate comparable or better accuracy to traditional risk tools with little or no improvement when adding clinical risk factor data. Transitioning from clinical risk factor-based to AI image-based risk models may lead to more accurate, personalized risk-based screening approaches., (Copyright © 2023 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Competing Interests: NH receives funding via a National Breast Cancer Foundation Chair in Breast Cancer Prevention grant (EC-21-001) and National Health and Medical Research Council Investigator (Leader) grant (1194410). MLM receives funding via a National Breast Cancer Foundation Investigator Initiated Research Scheme grant (IIRS-20-011).

Objective: This follow-up study of BreastScreen Victoria's pilot trial of digital breast tomosynthesis aimed to report interval cancer rates, screening sensitivity, and density-stratified outcomes for tomosynthesis vs mammography screening., Methods: Prospective pilot trial [ACTRN-12617000947303] in Maroondah BreastScreen recruited females ≥ 40 years presenting for screening (August 2017-November 2018) to DBT; concurrent screening participants who received mammography formed a comparison group. Follow-up of 24 months from screen date was used to ascertain interval cancers; automated breast density was measured., Results: There were 48 screen-detected and 9 interval cancers amongst 4908 tomosynthesis screens, and 34 screen-detected and 16 interval cancers amongst 5153 mammography screens. Interval cancer rate was 1.8/1000 (95%CI 0.8-3.5) for tomosynthesis vs 3.1/1000 (95%CI 1.8-5.0) for mammography ( p = 0.20). Sensitivity of tomosynthesis (86.0%; 95% CI 74.2-93.7) was significantly higher than mammography (68.0%; 95% CI 53.3-80.5), p = 0.03. Cancer detection rate (CDR) of 9.8/1000 (95%CI 7.2-12.9) for tomosynthesis was higher than that of 6.6/1000 (95%CI 4.6-9.2) for mammography ( p = 0.08); density-stratified analyses showed CDR was significantly higher for tomosynthesis than mammography (10.6/1000 vs 3.5/1000, p = 0.03) in high-density screens. Recall rate for tomosynthesis was significantly higher than for mammography (4.2% vs  3.0%, p < 0.001), and this increase in recall for tomosynthesis was evident only in high-density screens (5.6% vs  2.9%, p < 0.001)., Conclusion: Although interval cancer rates did not significantly differ between screened groups, sensitivity was significantly higher for tomosynthesis than mammography screening., Advances in Knowledge: In a program-embedded pilot trial, both increased cancer detection and recall rates from tomosynthesis were predominantly observed in high-density screens.

Background: A 2014 SSO-ASTRO guideline on surgical margins aimed to reduce unnecessary reoperation after breast conserving surgery (BCS). We investigate whether publication of the guideline was associated with a reduction in reoperation in Western Australia (WA)., Methods: In this retrospective, population-based cohort study, cases of newly-diagnosed breast cancer were identified from the WA Cancer Registry. Linkage to the Hospital Morbidity Data Collection identified index BCS for invasive cancer between January 2009 and June 2018 (N = 8059) and reoperation within 90 days. Pre-guideline (2009-2013) and post-guideline (2014-2018) reoperation proportions were compared, and temporal trends were estimated with generalised linear regression., Results: The pre-guideline reoperation proportion was 25.8% compared with 21.7% post-guideline (difference -4.0% [95% CI -5.9, -2.2, p < 0.001], odds ratio [OR] 0.80 [95% CI 0.72, 0.89, p < 0.001]). Absolute reductions were similar for repeat BCS (16.3% versus 14.6%; difference -1.8% [95% CI -3.4, -0.2, p = 0.03]) and conversion to mastectomy (9.4% versus 7.2%; difference -2.2% [95% CI -3.4, -1.0, p < 0.001]). Over the study period, there was an annual absolute change in reoperation of -0.8% (95% CI -1.2, -0.5, p < 0.001). Accounting for this linear trend, the difference in reoperation between time periods was -0.5% (95% CI -4.3, 3.3; p = 0.81), reflecting a non-significant reduction in conversion to mastectomy., Conclusions: Comparisons of pre- versus post-guideline time periods in WA showed reductions in reoperation that were similar to international estimates; however, an annual decline in reoperation predated the guideline. Analyses that do not account for temporal trends are likely to overestimate changes in reoperation associated with the guideline., Competing Interests: Declaration of competing interest MLM and NH contributed to the meta-analyses that supported the SSO/ASTRO guideline. NH contributed to the development of the SSO/ASTRO guideline. The other authors declare no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Artificial intelligence (AI) has been proposed to reduce false-positive screens, increase cancer detection rates (CDRs), and address resourcing challenges faced by breast screening programs. We compared the accuracy of AI versus radiologists in real-world population breast cancer screening, and estimated potential impacts on CDR, recall and workload for simulated AI-radiologist reading., Methods: External validation of a commercially-available AI algorithm in a retrospective cohort of 108,970 consecutive mammograms from a population-based screening program, with ascertained outcomes (including interval cancers by registry linkage). Area under the ROC curve (AUC), sensitivity and specificity for AI were compared with radiologists who interpreted the screens in practice. CDR and recall were estimated for simulated AI-radiologist reading (with arbitration) and compared with program metrics., Findings: The AUC for AI was 0.83 compared with 0.93 for radiologists. At a prospective threshold, sensitivity for AI (0.67; 95% CI: 0.64-0.70) was comparable to radiologists (0.68; 95% CI: 0.66-0.71) with lower specificity (0.81 [95% CI: 0.81-0.81] versus 0.97 [95% CI: 0.97-0.97]). Recall rate for AI-radiologist reading (3.14%) was significantly lower than for the BSWA program (3.38%) (-0.25%; 95% CI: -0.31 to -0.18; P < 0.001). CDR was also lower (6.37 versus 6.97 per 1000) (-0.61; 95% CI: -0.77 to -0.44; P < 0.001); however, AI detected interval cancers that were not found by radiologists (0.72 per 1000; 95% CI: 0.57-0.90). AI-radiologist reading increased arbitration but decreased overall screen-reading volume by 41.4% (95% CI: 41.2-41.6)., Interpretation: Replacement of one radiologist by AI (with arbitration) resulted in lower recall and overall screen-reading volume. There was a small reduction in CDR for AI-radiologist reading. AI detected interval cases that were not identified by radiologists, suggesting potentially higher CDR if radiologists were unblinded to AI findings. These results indicate AI's potential role as a screen-reader of mammograms, but prospective trials are required to determine whether CDR could improve if AI detection was actioned in double-reading with arbitration., Funding: National Breast Cancer Foundation (NBCF), National Health and Medical Research Council (NHMRC)., Competing Interests: Declaration of interests WL is a consultant for DeepHealth, RadNet AI Solutions, was a full-time employee during conduct of this study, and owns stock in that entity. Other authors have no competing interest to declare., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Breast cancer care has been affected by the COVID-19 pandemic. This systematic review aims to describe the observed pandemic-related changes in clinical and health services outcomes for breast screening and diagnosis., Methods: Seven databases (January 2020-March 2021) were searched to identify studies of breast cancer screening or diagnosis that reported observed outcomes before and related to the pandemic. Findings were presented using a descriptive and narrative approach., Results: Seventy-four studies were included in this systematic review; all compared periods before and after (or fluctuations during) the pandemic. None were assessed as being at low risk of bias. A reduction in screening volumes during the pandemic was found with over half of studies reporting reductions of ≥49%. A majority (66%) of studies reported reductions of ≥25% in the number of breast cancer diagnoses, and there was a higher proportion of symptomatic than screen-detected cancers. The distribution of cancer stage at diagnosis during the pandemic showed lower proportions of early-stage (stage 0-1/I-II, or Tis and T1) and higher proportions of relatively more advanced cases than that in the pre-pandemic period, however population rates were generally not reported., Conclusions: Evidence of substantial reductions in screening volume and number of diagnosed breast cancers, and higher proportions of advanced stage cancer at diagnosis were found during the pandemic. However, these findings reflect short term outcomes, and higher-quality research examining the long-term impact of the pandemic is needed., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: We examined whether digital breast tomosynthesis (DBT) detects differentially in high- or low-density screens., Methods: We searched six databases (2009-2020) for studies comparing DBT and digital mammography (DM), and reporting cancer detection rate (CDR) and/or recall rate by breast density. Meta-analysis was performed to pool incremental CDR and recall rate for DBT (versus DM) for high- and low-density (dichotomised based on BI-RADS) and within-study differences in incremental estimates between high- and low-density. Screening settings (European/US) were compared., Results: Pooled within-study difference in incremental CDR for high- versus low-density was 1.0/1000 screens (95% CI: 0.3, 1.6; p = 0.003). Estimates were not significantly different in US (0.6/1000; 95% CI: 0.0, 1.3; p = 0.05) and European (1.9/1000; 95% CI: 0.3, 3.5; p = 0.02) settings (p for subgroup difference = 0.15). For incremental recall rate, within-study differences between density subgroups differed by setting (p < 0.001). Pooled incremental recall was less in high- versus low-density screens (-0.9%; 95% CI: -1.4%, -0.4%; p < 0.001) in US screening, and greater (0.8%; 95% CI: 0.3%, 1.3%; p = 0.001) in European screening., Conclusions: DBT has differential incremental cancer detection and recall by breast density. Although incremental CDR is greater in high-density, a substantial proportion of additional cancers is likely to be detected in low-density screens. Our findings may assist screening programmes considering DBT for density-tailored screening., (© 2022. The Author(s).)

Objectives: To determine screening outcomes in women who have no recorded risk factors for breast cancer., Methods: A retrospective population-based cohort study included all 1,026,137 mammography screening episodes in 323,082 women attending the BreastScreen Western Australia (part of national biennial screening) program between July 2007 and June 2017. Cancer detection rates (CDR) and interval cancer rates (ICR) were calculated in screening episodes with no recorded risk factors for breast cancer versus at least one risk factor stratified by age. CDR was further stratified by timeliness of screening (<27 versus ≥27 months); ICR was stratified by breast density., Results: Amongst 566,948 screens (55.3%) that had no recorded risk factors, 2347 (40.9%) screen-detected cancers were observed. In screens with no risk factors, CDR was 50 (95%CI 48-52) per 10,000 screens and ICR was 7.9 (95%CI 7.4-8.4) per 10,000 women-years, estimates that were lower than screens with at least one risk factor (CDR 83 (95%CI 80-86) per 10,000 screens, ICR 12.2 (95%CI 11.5-13.0) per 10,000 women-years). Compared to timely screens with risk factors, delayed screens with no risk factors had similar CDR across all age groups and a higher proportion of node positive cancers (26.1% vs 20.7%). ICR was lowest in screens that had no risk factors nor dense breasts in all age groups., Conclusions: Majority of screens had no recorded breast cancer risk factors, hence a substantial proportion of screen-detected cancers occur in these screening episodes. Our findings may not justify less frequent screening in women with no risk factors., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: The aim of this study was to describe the current state of science regarding independent external validation of artificial intelligence (AI) technologies for screening mammography., Methods: A systematic review was performed across five databases (Embase, PubMed, IEEE Explore, Engineer Village, and arXiv) through December 10, 2020. Studies that used screening examinations from real-world settings to externally validate AI algorithms for mammographic cancer detection were included. The main outcome was diagnostic accuracy, defined by area under the receiver operating characteristic curve (AUC). Performance was also compared between radiologists and either stand-alone AI or combined radiologist and AI interpretation. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool., Results: After data extraction, 13 studies met the inclusion criteria (148,361 total patients). Most studies (77% [n = 10]) evaluated commercially available AI algorithms. Studies included retrospective reader studies (46% [n = 6]), retrospective simulation studies (38% [n = 5]), or both (15% [n = 2]). Across 5 studies comparing stand-alone AI with radiologists, 60% (n = 3) demonstrated improved accuracy with AI (AUC improvement range, 0.02-0.13). All 5 studies comparing combined radiologist and AI interpretation with radiologists alone demonstrated improved accuracy with AI (AUC improvement range, 0.028-0.115). Most studies had risk for bias or applicability concerns for patient selection (69% [n = 9]) and the reference standard (69% [n = 9]). Only two studies obtained ground-truth cancer outcomes through regional cancer registry linkage., Conclusions: To date, external validation efforts for AI screening mammographic technologies suggest small potential diagnostic accuracy improvements but have been retrospective in nature and suffer from risk for bias and applicability concerns., (Copyright © 2021 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Introduction: Artificial intelligence (AI) algorithms for interpreting mammograms have the potential to improve the effectiveness of population breast cancer screening programmes if they can detect cancers, including interval cancers, without contributing substantially to overdiagnosis. Studies suggesting that AI has comparable or greater accuracy than radiologists commonly employ 'enriched' datasets in which cancer prevalence is higher than in population screening. Routine screening outcome metrics (cancer detection and recall rates) cannot be estimated from these datasets, and accuracy estimates may be subject to spectrum bias which limits generalisabilty to real-world screening. We aim to address these limitations by comparing the accuracy of AI and radiologists in a cohort of consecutive of women attending a real-world population breast cancer screening programme., Methods and Analysis: A retrospective, consecutive cohort of digital mammography screens from 109 000 distinct women was assembled from BreastScreen WA (BSWA), Western Australia's biennial population screening programme, from November 2016 to December 2017. The cohort includes 761 screen-detected and 235 interval cancers. Descriptive characteristics and results of radiologist double-reading will be extracted from BSWA outcomes data collection. Mammograms will be reinterpreted by a commercial AI algorithm (DeepHealth). AI accuracy will be compared with that of radiologist single-reading based on the difference in the area under the receiver operating characteristic curve. Cancer detection and recall rates for combined AI-radiologist reading will be estimated by pairing the first radiologist read per screen with the AI algorithm, and compared with estimates for radiologist double-reading., Ethics and Dissemination: This study has ethical approval from the Women and Newborn Health Service Ethics Committee (EC00350) and the Curtin University Human Research Ethics Committee (HRE2020-0316). Findings will be published in peer-reviewed journals and presented at national and international conferences. Results will also be disseminated to stakeholders in Australian breast cancer screening programmes and policy makers in population screening., Competing Interests: Competing interests: WL and JGK are employees of RadNet, the parent company of DeepHealth. CL reports textbook royalties from McGraw Hill, Wolters Kluwer, and Oxford University Press; and research consulting fees from GRAIL, all outside the submitted work. SZ reports speaker fees from Siemens Healthcare AG. Other authors have no competing interest to declare., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

This study assessed symptoms of anxiety, depression and fear of COVID-19 in members of the general community and healthcare workers (HCWs) attending for COVID testing. This cross-sectional study was conducted in a public hospital COVID-19 testing clinic (June-September 2020) using self-administered questionnaires (i.e. the Hospital Anxiety and Depression Scale (HADS) and the Fear of COVID-19 Scale). In all, 430 participants who met the criteria for COVID-19 testing with nasopharyngeal and throat swabs completed the questionnaires. The mean (±s.d.) age of participants was 37.6 ± 12.6 years. HCWs made up 35.1% of the sample. Overall, the mean (±s.d.) score for anxiety was 6.09 ± 4.41 and 'case' prevalence (any severity) was 151/430 (35.1%), higher than normative population scores. Higher anxiety was found in women (P = 0.001) and in clients who had previously been tested for coronavirus (P = 0.03). HCWs had lower anxiety scores than members of the general community (P = 0.001). For depression, the mean (±s.d.) score was 4.18 ± 3.60, with a 'case' prevalence (any severity) of 82/430 (19.1%), similar to normative population scores. Women reported a higher level of COVID-19 fear (P = 0.001), as did people with a lower education level (P = 0.001). A greater psychological impact of COVID-19 was observed in women, people undergoing repeat testing and participants reporting lower levels of educational attainment. HCWs had fewer symptoms of anxiety and depression than non-HCWs attending the same clinic for COVID-19 testing. This information can be used to plan mental health interventions in primary care and testing settings during this and future pandemics.

Objectives: To estimate rates of screen-detected and interval breast cancers, stratified by risk factor, to inform discussions of risk-stratified population screening., Design: Retrospective population-based cohort study; analysis of routinely collected BreastScreen WA program clinical and administrative data., Setting, Participants: All BreastScreen WA mammography screening episodes for women aged 40 years or more during 1 July 2007 - 30 June 2017., Main Outcome Measures: Cancer detection rate (CDR) and interval cancer rate (ICR), by risk factor., Results: A total of 323 082 women were screened in 1 026 137 screening episodes (mean age, 58.5 years; SD, 8.6 years). The overall CDR was 68 (95% CI, 67-70) cancers per 10 000 screens, and the overall ICR was 9.7 (95% CI, 9.2-10.1) cancers per 10 000 women-years. Interactions between the effects on CDR of age group and five risk factors were statistically significant: personal history of breast cancer (P = 0.039), family history of breast cancer (P = 0.005), risk-relevant benign conditions (P = 0.012), hormone-replacement therapy (P = 0.002), and self-reported symptoms (P < 0.001). The influence of these risk factors (except personal history) increased with age. For ICR, only the interaction between age and hormone-replacement therapy was significant (P < 0.001), although weak interactions between age and family history of breast cancer or having dense breasts were noted (each P = 0.07). The influence of family history on ICR was significant only for women aged 40-49 years., Conclusions: Screening CDR and (for some risk factors) ICR were higher for women in some age groups with personal histories of breast cancer or risk-relevant benign breast conditions or first degree family history of breast cancer, women with dense breasts or self-reported breast-related symptoms, and women using hormone-replacement therapy. Our findings could inform the evaluation of risk-based screening., (© 2021 The Authors. Medical Journal of Australia published by John Wiley & Sons Australia, Ltd on behalf of AMPCo Pty Ltd.)

Background: In patients with triple-negative breast cancer (TNBC), oncological and survival outcomes based on locoregional treatment are poorly understood. In particular, the safety of breast-conserving surgery (BCS) for TNBC has been questioned., Methods: A meta-analysis was performed to evaluate locoregional recurrence (LRR), distant metastasis (DM), and overall survival (OS) rates in patients with TNBC who had breast-conserving surgery versus mastectomy. Estimates were pooled in random-effects analysis. The effect of study-level co-variables was assessed by univariable metaregression., Results: Fourteen studies, including 19 819 patients operated for TNBC met the inclusion criteria; 9828 patients (49.6 per cent) underwent BCS and 9991 (50.4 per cent) had a mastectomy. Patients with smaller tumours were more likely to be selected for BCS (pooled odds ratio (OR) for T1 tumours 1.95, 95 per cent c.i. 1.64 to 2.32; P < 0.001). The pooled OR for LRR was 0.64 (0.48 to 0.85; P = 0.002), indicating a statistically significantly lower odds of LRR among women who had BCS relative to mastectomy. The pooled OR for DM was 0.70 (0.53 to 0.94; P = 0.02), indicating a lower odds of DM among women who had BCS; however, this difference diminished with increasing study-level age and follow-up time. A pooled hazard ratio of 0.78 (0.69 to 0.89; P < 0.001) showed a significantly lower hazard for all-cause mortality among women undergoing BCS versus mastectomy., Conclusion: These results should be interpreted cautiously owing to likely differences in selection for BCS or mastectomy in the included studies. Patients with TNBC selected for BCS do not, however, have a worse prognosis than those treated with mastectomy, and breast conservation can be offered when feasible clinically., (© The Author(s) 2021. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: The aim was to determine the cost-effectiveness of radioguided occult lesion localization using 125I-labelled seeds (125I seeds) versus hookwire localization in terms of incremental cost per reoperation avoided for women with non-palpable breast cancer undergoing breast-conserving surgery., Methods: This study was based on a multicentre RCT with eight study sites comprising seven public hospitals and one private hospital. An Australian public health system perspective was taken. The primary effectiveness outcome for this study was reoperations avoided. Cost-effectiveness was expressed as an incremental cost-effectiveness ratio (ICER). One-way and probabilistic sensitivity analyses were used to explore uncertainty. The willingness to pay (additional cost of localization using 125I seeds justified by reoperation cost avoided) was set at the weighted, top-down cost of reoperation. Costs were in 2019 Australian dollars ($1 was equivalent to €0.62)., Results: The reoperation rate was 13.9 (95 per cent confidence interval 10.7 to 18.0) per cent for the 125I seed group and 18.9 (14.8 to 23.8) per cent for the hookwire localization group. The ICER for 125I seed versus hookwire localization was $4474 per reoperation averted. The results were most sensitive to uncertainty around the probability of reoperation. Accounting for transition probability and cost uncertainty for 125I seed localization, there was a 77 per cent probability that using 125I seeds would be cost-effective, with a willingness to pay of $7693 per reoperation averted., Conclusion: Radioguided occult lesion localization using 125I seeds is likely to be cost-effective, because the marginal (additional) cost compared with hookwire localization is less than the cost of reoperations avoided., (© The Author(s) 2021. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Most evidence for interpregnancy interval (IPI) and adverse birth outcomes come from studies that are prone to incomplete control for confounders that vary between women. Comparing pregnancies to the same women can address this issue., Methods: We conducted an international longitudinal cohort study of 5,521,211 births to 3,849,193 women from Australia (1980-2016), Finland (1987-2017), Norway (1980-2016) and the United States (California) (1991-2012). IPI was calculated based on the time difference between two dates-the date of birth of the first pregnancy and the date of conception of the next (index) pregnancy. We estimated associations between IPI and preterm birth (PTB), spontaneous PTB, and small-for-gestational age births (SGA) using logistic regression (between-women analyses). We also used conditional logistic regression comparing IPIs and birth outcomes in the same women (within-women analyses). Random effects meta-analysis was used to calculate pooled adjusted odds ratios (aOR)., Results: Compared to an IPI of 18-23 months, there was insufficient evidence for an association between IPI <6 months and overall PTB (aOR 1.08, 95% CI 0.99-1.18) and SGA (aOR 0.99, 95% CI 0.81-1.19), but increased odds of spontaneous PTB (aOR 1.38, 95% CI 1.21-1.57) in the within-women analysis. We observed elevated odds of all birth outcomes associated with IPI ≥60 months. In comparison, between-women analyses showed elevated odds of adverse birth outcomes for <12 month and >24 month IPIs., Conclusions: We found consistently elevated odds of adverse birth outcomes following long IPIs. IPI shorter than 6 months were associated with elevated risk of spontaneous PTB, but there was insufficient evidence for increased risk of other adverse birth outcomes. Current recommendations of waiting at least 24 months to conceive after a previous pregnancy, may be unnecessarily long in high-income countries., Competing Interests: The authors have declared that no competing interests exist.

Background: Despite extensive research on risk factors and mechanisms, the extent to which interpregnancy interval (IPI) affects hypertensive disorders of pregnancy in high-income countries remains unclear., Objectives: To examine the association between IPI and hypertensive disorders of pregnancy in a high-income country setting using both within-mother and between-mother comparisons., Methods: A retrospective population-based cohort study was conducted among 103 909 women who delivered three or more consecutive singleton births (n = 358 046) between 1980 and 2015 in Western Australia. We used conditional Poisson regression with robust variance, matching intervals of the same mother and adjusted for factors that vary within-mother across pregnancies, to investigate the association between IPI categories (reference 18-23 months), and the risk of hypertensive disorders of pregnancy. For comparison with previous studies, we also applied unmatched Poisson regression (between-mother analysis)., Results: The incidence of preeclampsia and gestational hypertension during the study period was 4%, and 2%, respectively. For the between-mother comparison, mothers with intervals of 6-11 months had lower risk of preeclampsia with adjusted relative risk (RR) 0.92 (95% confidence interval [CI] 0.85, 0.98) compared to reference category of 18-23 months. With the within-mother matched design, we estimated a larger effect of long IPI on risk of preeclampsia (RR 1.29, 95% CI 1.18, 1.42 for 60-119 months; and RR 1.30, 95% CI 1.10, 1.53 for intervals ≥120 months) compared to 18-23 months. Short IPIs were not associated with hypertensive disorders of pregnancy., Conclusions: In our cohort, longer IPIs were associated with increased risk of preeclampsia. However, there was insufficient evidence to suggest that short IPIs (<6 months) increase the risks of hypertensive disorders of pregnancy., (© 2020 John Wiley & Sons Ltd.)

Background: Previous studies have suggested improved efficiency and patient outcomes with 125I seed compared with hookwire localization (HWL) in breast-conserving surgery, but high-level evidence of superior surgical outcomes is lacking. The aim of this multicentre pragmatic RCT was to compare re-excision and positive margin rates after localization using 125I seed or hookwire in women with non-palpable breast cancer., Methods: Between September 2013 and March 2018, women with non-palpable breast cancer eligible for breast-conserving surgery were assigned randomly to preoperative localization using 125I seeds or hookwires. Randomization was stratified by lesion type (pure ductal carcinoma in situ (DCIS) or other) and study site. Primary endpoints were rates of re-excision and margin positivity. Secondary endpoints were resection volumes and weights., Results: A total of 690 women were randomized at eight sites; 659 women remained after withdrawal (125I seed, 327; HWL, 332). Mean age was 60.3 years in the 125I seed group and 60.7 years in the HWL group, with no difference between the groups in preoperative lesion size (mean 13.2 mm). Lesions were pure DCIS in 25.9 per cent. The most common radiological lesion types were masses (46.9 per cent) and calcifications (28.2 per cent). The localization modality was ultrasonography in 65.5 per cent and mammography in 33.7 per cent. The re-excision rate after 125I seed localization was significantly lower than for HWL (13.9 versus 18.9 per cent respectively; P = 0.019). There were no significant differences in positive margin rates, or in specimen weights and volumes., Conclusion: Re-excision rates after breast-conserving surgery were significantly lower after 125I seed localization compared with HWL. Registration number: ACTRN12613000655741 (http://www.ANZCTR.org.au/)., (© The Author(s) 2020. Published by Oxford University Press on behalf of BJS Society Ltd.)

Background: Breast screening programs replaced film mammography with digital mammography, and the effects of this practice shift in population screening on health outcomes can be measured through examination of cancer detection and interval cancer rates., Methods: A systematic review and random effects meta-analysis were undertaken. Seven databases were searched for publications that compared film with digital mammography within the same population of asymptomatic women and reported cancer detection and/or interval cancer rates., Results: The analysis included 24 studies with 16 583 743 screening examinations (10 968 843 film and 5 614 900 digital). The pooled difference in the cancer detection rate showed an increase of 0.51 per 1000 screens (95% confidence interval [CI] = 0.19 to 0.83), greater relative increase for ductal carcinoma in situ (25.2%, 95% CI = 17.4% to 33.5%) than invasive (4%, 95% CI = -3% to 13%), and a recall rate increase of 6.95 (95% CI = 3.47 to 10.42) per 1000 screens after the transition from film to digital mammography. Seven studies (80.8% of screens) reported interval cancers: the pooled difference showed no change in the interval cancer rate with -0.02 per 1000 screens (95% CI = -0.06 to 0.03). Restricting analysis to studies at low risk of bias resulted in findings consistent with the overall pooled results for all outcomes., Conclusions: The increase in cancer detection following the practice shift to digital mammography did not translate into a reduction in the interval cancer rate. Recall rates were increased. These results suggest the transition from film to digital mammography did not result in health benefits for screened women. This analysis reinforces the need to carefully evaluate effects of future changes in technology, such as tomosynthesis, to ensure new technology leads to improved health outcomes and beyond technical gains., (© The Author(s) 2020. Published by Oxford University Press.)

Importance: The 2014 publication of the Society of Surgical Oncology-American Society for Radiation Oncology (SSO-ASTRO) Consensus Guideline on Margins for Breast-Conserving Surgery recommended a negative margin definition of no ink on tumor. Adoption of this guideline would represent a major change in surgical practice that could lower the rates of reoperation., Objective: To assess changes in reoperation rates after publication of the SSO-ASTRO guideline., Data Sources: A systematic search of Embase, PREMEDLINE, Evidence-Based Medicine Reviews, Scopus, and Web of Science for biomedical literature published from January 2014 to July 2019 was performed. This search was supplemented by web searches and manual searching of conference abstracts., Study Selection: Included studies compared the reoperation rates in preguideline vs postguideline cohorts (actual change), retrospectively applied the SSO-ASTRO guideline to a preguideline cohort (projected change), or described the economic outcomes of the guideline., Data Extraction and Synthesis: Study characteristics and reoperation rates were extracted independently by 2 reviewers. Odds ratios (ORs) were pooled by random effects meta-analysis. Analyses were stratified by study setting (institutional or population) and preguideline accepted margins. The economic outcomes of the guideline were summarized narratively. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed., Main Outcomes and Measures: Odds ratios for postguideline vs preguideline reoperation rates., Results: From 1114 citations, 30 studies (with 599 016 participants) reported changes in reoperation rates. Studies included a median (range) of 487 (100-521 578) participants, and 20 studies were undertaken in the US, 6 in the UK, 3 in Canada, and 1 in Australia. Among 21 studies of actual changes, pooled ORs showed a statistically significant reduction in reoperation, with an OR lower in institution-based studies than in population-based studies (OR, 0.62 [95% CI, 0.52-0.74] vs 0.76 [95% CI, 0.72-0.80]; P = .04 for subgroup differences). Among 9 studies of projected changes, the pooled OR was lower for preguideline margin thresholds of 2 mm or more compared with 1 mm (OR, 0.47 [95% CI, 0.40-0.56] vs 0.85 [95% CI, 0.79-0.91; P < .001 for subgroup differences). Projected changes were likely to overestimate actual changes. Six studies that estimated the postguideline economic outcome found the guideline to be potentially cost saving, with a median (range) saving of US $3540 ($1800-$25 650) per woman avoiding reoperation., Conclusions and Relevance: This study found a decrease in reoperation rates after the publication of the SSO-ASTRO guideline; this reduction was greater at an institutional level than a population level, the latter reflecting the differences in guideline adoption between centers. These early outcomes may be conservative estimates of longer-term implications.

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression.

Purpose: To examine the association between interpregnancy interval (IPI) and gestational diabetes using both within-mother and between-mother comparisons., Methods: A retrospective cohort study of 103,909 women who delivered three or more consecutive singleton births (n = 358,046) between 1 January 1980 and 31 December 2015 in Western Australia. The association between IPI and gestational diabetes was estimated using conditional logistic regression, matching pregnancies to the same mother and adjusted for factors that vary within-mother across pregnancies. For comparison with previous studies, we also applied unmatched logistic regression (between-mother analysis)., Results: The conventional between-mother analysis resulted in adjusted odds ratios (aOR) of 1.13 (95% CI, 1.06-1.21) for intervals of 24-59 months and 1.51 (95% CI, 1.33-1.70) for intervals of 120 or more months, compared with IPI of 18-23 months. In addition, short IPIs were associated with lower odds of gestational diabetes with (aOR: 0.89; 95% CI, 0.82-0.97) for 6-11 months and (aOR: 0.92; 95% CI, 0.85-0.99) for 12-17-month. In comparison, the adjusted within-mother matched analyses showed no statistically significant association between IPIs and gestational diabetes. All effect estimates were attenuated using the within-mother matched model., Conclusion: Our findings do not support the hypothesis that short IPI (<6 months) increases the risk of gestational diabetes and suggest that observed associations in previous research might be attributable to confounders that vary between mothers., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: Tomosynthesis is proposed to improve breast cancer assessment and staging. We compared tomosynthesis and mammography in estimating the size of newly-diagnosed breast cancers., Methods: All pathologically-confirmed cancers detected in the STORM-2 trial (90 cancers, 85 women) were retrospectively measured on tomosynthesis by two independent readers. One reader also measured cancers on mammography. Relative mean differences (MDs) and 95% limits of agreement (LOA) with pathology were estimated for tomosynthesis and mammography within a single reader (Analysis 1) and between two readers (Analysis 2)., Results: Where cancers were detected and hence measured by both tests, tomosynthesis overestimated pathologic size relative to mammography (Analysis 1: MD 5% versus 1%, Analysis 2: 7% versus 3%; P = 0.10 both analyses). There was similar, large measurement variability for both tests (LOA range: -60% to +166%). Overestimation by tomosynthesis was attributable to the subgroup with dense breasts (MDs = 12-13% versus 4% for mammography). There was low average bias for both tests in the low-density subgroup (MDs = 0-4%). LOA were larger in dense breasts for both tomosynthesis and mammography (P ≤ 0.02 all comparisons). Cancers detected only by tomosynthesis were more frequently in dense breasts (60-68%): for those tumours size was estimated with increased measurement variability (LOA ranging from -75% to +293%)., Conclusions: On average, tomosynthesis overestimates pathologic tumour size in women with dense breasts; that difference is more likely to impact management in women with larger tumours. The main advantage of tomosynthesis appears to be detecting mammographically-occult cancers; however tomosynthesis less accurately measured those cancers in dense breasts (large measurement variability)., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Introduction: Short interpregnancy interval (IPI) has been linked to adverse pregnancy outcomes. WHO recommends waiting at least 2 years after a live birth and 6 months after miscarriage or induced termination before conception of another pregnancy. The evidence underpinning these recommendations largely relies on data from low/middle-income countries. Furthermore, recent epidemiological investigations have suggested that these studies may overestimate the effects of IPI due to residual confounding. Future investigations of IPI effects in high-income countries drawing from large, population-based data sources are needed to inform IPI recommendations. We aim to assess the impact of IPIs on maternal and child health outcomes in high-income countries., Methods and Analysis: This international longitudinal retrospective cohort study will include more than 18 million pregnancies, making it the largest study to investigate IPI in high-income countries. Population-based data from Australia, Finland, Norway and USA will be used. Birth records in each country will be used to identify consecutive pregnancies. Exact dates of birth and clinical best estimates of gestational length will be used to estimate IPI. Administrative birth and health data sources with >99% coverage in each country will be used to identify maternal sociodemographics, pregnancy complications, details of labour and delivery, birth and child health information. We will use matched and unmatched regression models to investigate the impact of IPI on maternal and infant outcomes, and conduct meta-analysis to pool results across countries., Ethics and Dissemination: Ethics boards at participating sites approved this research (approval was not required in Finland). Findings will be published in peer-reviewed journals and presented at international conferences, and will inform recommendations for optimal IPI in high-income countries. Findings will provide important information for women and families planning future pregnancies and for clinicians providing prenatal care and giving guidance on family planning., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ.)

Background: Tomosynthesis approximates a 3D mammogram of the breast, reducing parenchymal overlap that masks cancers or creates false "lesions" on 2D mammography, and potentially enabling more accurate detection of breast cancer. We compared breast cancer screening detection and recall in asymptomatic women for tomosynthesis vs 2D mammography., Methods: A systematic review and random effects meta-analysis were undertaken. Electronic databases (2009-July 2017) were searched for studies comparing tomosynthesis and 2D mammography in asymptomatic women who attended population breast cancer screening and reporting cancer detection rate (CDR) and recall rate. All statistical tests were two-sided., Results: Seventeen studies (1 009 790 participants) were included from 413 citations. The pooled incremental CDR for tomosynthesis was 1.6 cancers per 1000 screens (95% confidence interval [CI] = 1.1 to 2.0, P < .001, I2 = 36.9%). Incremental CDR was statistically significantly higher for European/Scandinavian studies, all using a "paired" design where women had both tests (2.4 per 1000 screens, 95% CI = 1.9 to 2.9, P < .001, I2 = 0.0%) compared with US ("unpaired") studies (1.1 per 1000 screens, 95% CI = 0.8 to 1.5, P < .001, I2 = 0.0%; P < .001 between strata). The recall rate for tomosynthesis was statistically significantly lower than for 2D mammography (pooled absolute reduction = -2.2%, 95% CI = -3.0 to -1.4, P < .001, I2 = 98.2%). Stratified analyses showed a decrease in US studies (pooled difference in recall rate = -2.9%, 95% CI = -3.5 to -2.4, P < .001, I2 = 92.9%) but not European/Scandinavian studies (0.5% increase in recall, 95% CI = -0.1 to 1.2, P = .12, I2 = 93.5%; P < .001 between strata). Results were similar in sensitivity analyses excluding studies with overlapping cohorts., Conclusions: Tomosynthesis improves CDR and reduces recall; however, effects are dependent on screening setting, with greater improvement in CDR in European/Scandinavian studies (biennial screening) and reduction in recall in US studies with high baseline recall.

Introduction: Interpregnancy interval (IPI) is the length of time between a birth and conception of the next pregnancy. Evidence suggests that both short and long IPIs are at increased risk of adverse pregnancy and perinatal outcomes. Relatively less attention has been directed towards investigating the effect of IPI on pregnancy complications, and the studies that have been conducted have shown mixed results.This systematic review will aim to provide an update to the most recent available evidence on the effect of IPI on pregnancy complications., Method and Analysis: We will search electronic databases such as Ovid/MEDLINE, EMBASE, CINAHL, Scopus, Web of Science and PubMed to identify peer-reviewed articles on the effects of IPI on pregnancy complications. We will include articles published from start of indexing until 12 February 2018 without any restriction to geographic setting. We will limit the search to literature published in English language and human subjects. Two independent reviewers will screen titles and abstracts and select full-text articles that meet the eligibility criteria. The Newcastle-Ottawa tool will be used to assess quality of observational studies. Where data permit, meta-analyses will be performed for individual pregnancy complications. A subgroup analyses by country categories (high-income vs low and middle-income countries) based on World Bank income group will be performed. Where meta-analysis is not possible, we will provide a description of data without further attempt to quantitatively pool results., Ethics and Dissemination: Formal ethical approval is not required as primary data will not be collected. The results will be published in peer-reviewed journals and presented at national and international conferences., Prospero Registration Number: CRD42018088578., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Digital breast tomosynthesis (DBT) addresses some of the limitations of digital mammography (DM) by reducing the effect of overlapping tissue. Emerging data have shown that DBT increases breast cancer (BC) detection and reduces recall in BC screening programs. Studies have also suggested that DBT improves assessment of screen-recalled findings. Areas covered: Studies of DBT for population BC screening and those for assessment of screen-detected findings were reviewed to provide an up-to-date summary of the evidence on DBT in the screening setting. A systematic literature search was conducted for each of the topics; study-specific information and/or quantitative data on detection or accuracy were extracted and collated in tables. Expert commentary: The evidence on DBT for BC screening reinforces that DBT integrated with DM increases cancer detection rates compared to DM alone, although the extent of improved detection varied between studies. The effect of DBT on recall rates was heterogeneous with substantial reductions evident noticeably in retrospective comparative studies. The evidence on DBT for workup was sparse and those studies had limitations related to design and methods. Even though the majority showed improved specificity using DBT compared with conventional imaging, there was little evidence on how DBT impacts assessment outcomes.

Introduction: Tomosynthesis is proposed to improve breast cancer assessment and staging as a complementary role to its detection capability. We examine the accuracy of tomosynthesis in measuring tumor size relative to pathology and compared with other tests., Areas Covered: A systematic literature search identified studies of tomosynthesis in estimating the size of newly diagnosed breast cancers. Descriptive analyses were performed due to heterogeneity in patients, technology, and methods between studies. Eight studies were eligible (678 patients). Mean differences (MDs) between measurements (tomosynthesis-pathology) were generally small; overestimation (MDs of 1-3 mm) and underestimation (-1 mm) were reported. Limits of agreement (LOA) ranged between ±10 mm and ±28 mm. MDs did not differ in high and low breast densities. Large underestimation (-11 mm) and wide LOA (±41 mm) were reported for invasive lobular carcinoma. MDs and LOA were lower for tomosynthesis than mammography, but differences between tests were small., Expert Commentary: Although tomosynthesis is a promising technology for assessing breast cancer size, few studies in that context had limitations (small sample sizes, heterogeneous populations, and technologies). Studies using current technology and appropriate statistical methods are required to establish the magnitude of improvement in measurement accuracy, and patients for whom the test may be of most benefit.

Background Controversy exists regarding the optimal negative margin width for ductal carcinoma in situ (DCIS) treated with breast-conserving surgery and whole-breast irradiation (WBRT). Methods A multidisciplinary consensus panel used a meta-analysis of margin width and ipsilateral breast tumor recurrence (IBTR) from a systematic review of 20 studies including 7883 patients and other published literature as the evidence base for consensus. Results Negative margins halve the risk of IBTR compared with positive margins defined as ink on DCIS. A 2 mm margin minimizes the risk of IBTR compared with smaller negative margins. More widely clear margins do not significantly decrease IBTR compared with 2 mm margins. Negative margins less than 2 mm alone are not an indication for mastectomy, and factors known to impact rates of IBTR should be considered in determining the need for re-excision. Conclusion The use of a 2 mm margin as the standard for an adequate margin in DCIS treated with WBRT is associated with low rates of IBTR and has the potential to decrease re-excision rates, improve cosmetic outcome, and decrease health care costs. Clinical judgment should be used in determining the need for further surgery in patients with negative margins < 2 mm.

Purpose: There is no consensus on adequate negative margins in breast-conserving surgery (BCS) for ductal carcinoma in situ (DCIS). We systematically reviewed the evidence on margins in BCS for DCIS., Methods: A study-level meta-analysis of local recurrence (LR), microscopic margin status and threshold distance for negative margins. LR proportion was modeled using random-effects logistic meta-regression (frequentist) and network meta-analysis (Bayesian) that allows for multiple margin distances per study, adjusting for follow-up time., Results: Based on 20 studies (LR: 865 of 7883), odds of LR were associated with margin status [logistic: odds ratio (OR) 0.53 for negative vs. positive/close (p < 0.001); network: OR 0.45 for negative vs. positive]. In logistic meta-regression, relative to >0 or 1 mm, ORs for 2 mm (0.51), 3 or 5 mm (0.42) and 10 mm (0.60) showed comparable significant reductions in the odds of LR. In the network analysis, ORs relative to positive margins for 2 (0.32), 3 (0.30) and 10 mm (0.32) showed similar reductions in the odds of LR that were greater than for >0 or 1 mm (0.45). There was weak evidence of lower odds at 2 mm compared with >0 or 1 mm [relative OR (ROR) 0.72, 95 % credible interval (CrI) 0.47-1.08], and no evidence of a difference between 2 and 10 mm (ROR 0.99, 95 % CrI 0.61-1.64). Adjustment for covariates, and analyses based only on studies using whole-breast radiotherapy, did not change the findings., Conclusion: Negative margins in BCS for DCIS reduce the odds of LR; however, minimum margin distances above 2 mm are not significantly associated with further reduced odds of LR in women receiving radiation.

Background: Magnetic resonance imaging (MRI) may guide breast cancer surgery by measuring residual tumor size post-neoadjuvant chemotherapy (NAC). Accurate measurement may avoid overly radical surgery or reduce the need for repeat surgery. This individual patient data (IPD) meta-analysis examines MRI's agreement with pathology in measuring the longest tumor diameter and compares MRI with alternative tests., Methods: A systematic review of MEDLINE, EMBASE, PREMEDLINE, Database of Abstracts of Reviews of Effects, Heath Technology Assessment, and Cochrane databases identified eligible studies. Primary study authors supplied IPD in a template format constructed a priori. Mean differences (MDs) between tests and pathology (i.e. systematic bias) were calculated and pooled by the inverse variance method; limits of agreement (LOA) were estimated. Test measurements of 0.0 cm in the presence of pathologic residual tumor, and measurements >0.0 cm despite pathologic complete response (pCR) were described for MRI and alternative tests., Results: Eight studies contributed IPD (N = 300). The pooled MD for MRI was 0.0 cm (LOA: +/-3.8 cm). Ultrasound underestimated pathologic size (MD: -0.3 cm) relative to MRI (MD: 0.1 cm), with comparable LOA. MDs were similar for MRI (0.1 cm) and mammography (0.0 cm), with wider LOA for mammography. Clinical examination underestimated size (MD: -0.8 cm) relative to MRI (MD: 0.0 cm), with wider LOA. Tumors "missed" by MRI typically measured 2.0 cm or less at pathology; tumors >2.0 cm were more commonly "missed" by clinical examination (9.3 %). MRI measurements >5.0 cm occurred in 5.3 % of patients with pCR, but were more frequent for mammography (46.2 %)., Conclusions: There was no systematic bias in MRI tumor measurement, but LOA are large enough to be clinically important. MRI's performance was generally superior to ultrasound, mammography, and clinical examination, and it may be considered the most appropriate test in this setting. Test combinations should be explored in future studies.

Early assessment of response to neoadjuvant chemotherapy (NAC) for breast cancer allows therapy to be tailored; however, optimal response assessment methods have not been established. We estimated the accuracy of ultrasound (US) to predict pathologic complete response (pCR) using common response criteria and pCR definitions, and estimated incremental accuracy over known prognostic variables. Participants undergoing US after two cycles in the GeparTrio trial randomised to no change in NAC were eligible. US response by World Health Organisation (WHO) criteria (1D or 2D) and Response Evaluation Criteria In Solid Tumours (RECIST) was assessed. Four pCR definitions were applied. Sensitivity (correct prediction of pCR), specificity (correct prediction of no-pCR) and diagnostic odds ratios (DORs) were calculated. Areas under the curve (AUCs) were derived from logistic regression including patient variables with and without US. In 832 patients, DORs decreased as pCR definitions became less stringent (p = 0.01). For WHO-2D, DORs were as follows: 4.07 (ypT0,ypN0), 3.75 (ypT0/is,ypN0), 3.14 (ypT0/is,ypN+/-) and 2.65 (ypT0/is/1a,ypN+/-). DORs did not differ between US criteria (p = 0.60). High sensitivity and lower specificity were found for WHO-2D and RECIST; WHO-1D was highly specific with low sensitivity. Sensitivity was highest for WHO-2D predicting ypT0,ypN0 (sensitivity = 81.7%, specificity = 47.6% vs. 42.3% and 80.4% for WHO-1D). Adding US to models including patient variables (age, T-stage, histology and subtype) improved AUCs for predicting pCR by 2-3%. In conclusion, US accuracy is highest for predicting ypT0,ypN0, shown to be most prognostic of long-term survival. WHO-2D and RECIST maximise sensitivity; WHO-1D maximises specificity. US modestly improves the prediction of pCR by patient characteristics., (© 2014 UICC.)

Purpose: There is no consensus on what constitutes adequate negative margins in breast-conserving therapy (BCT). We systematically review the evidence on surgical margins in BCT for invasive breast cancer to support the development of clinical guidelines., Methods: Study-level meta-analysis of studies reporting local recurrence (LR) data relative to final microscopic margin status and the threshold distance for negative margins. LR proportion was modeled using random-effects logistic meta-regression., Results: Based on 33 studies (LR in 1,506 of 28,162), the odds of LR were associated with margin status [model 1: odds ratio (OR) 1.96 for positive/close vs negative; model 2: OR 1.74 for close vs. negative, 2.44 for positive vs. negative; (P < 0.001 both models)] but not with margin distance [model 1: >0 mm vs. 1 mm (referent) vs. 2 mm vs. 5 mm (P = 0.12); and model 2: 1 mm (referent) vs. 2 mm vs. 5 mm (P = 0.90)], adjusting for study median follow-up time. There was little to no statistical evidence that the odds of LR decreased as the distance for declaring negative margins increased, adjusting for follow-up time [model 1: 1 mm (OR 1.0, referent), 2 mm (OR 0.95), 5 mm (OR 0.65), P = 0.21 for trend; and model 2: 1 mm (OR 1.0, referent), 2 mm (OR 0.91), 5 mm (OR 0.77), P = 0.58 for trend]. Adjustment for covariates, such as use of endocrine therapy or median-year of recruitment, did not change the findings., Conclusions: Meta-analysis confirms that negative margins reduce the odds of LR; however, increasing the distance for defining negative margins is not significantly associated with reduced odds of LR, allowing for follow-up time. Adoption of wider relative to narrower margin widths to declare negative margins is unlikely to have a substantial additional benefit for long-term local control in BCT.

Background: Magnetic resonance imaging (MRI) has been proposed to guide breast cancer surgery by measuring residual tumour after neoadjuvant chemotherapy. This study-level meta-analysis examines MRI's agreement with pathology, compares MRI with alternative tests and investigates consistency between different measures of agreement., Methods: A systematic literature search was undertaken. Mean differences (MDs) in tumour size between MRI or comparator tests and pathology were pooled by assuming a fixed effect. Limits of agreement (LOA) were estimated from a pooled variance by assuming equal variance of the differences across studies., Results: Data were extracted from 19 studies (958 patients). The pooled MD between MRI and pathology from six studies was 0.1 cm (95% LOA: -4.2 to 4.4 cm). Similar overestimation for MRI (MD: 0.1 cm) and ultrasound (US) (MD: 0.1 cm) was observed, with comparable LOA (two studies). Overestimation was lower for MRI (MD: 0.1 cm) than mammography (MD: 0.4 cm; two studies). Overestimation by MRI (MD: 0.1 cm) was smaller than underestimation by clinical examination (MD: -0.3 cm). The LOA for mammography and clinical examination were wider than that for MRI. Percentage agreement between MRI and pathology was greater than that of comparator tests (six studies). The range of Pearson's/Spearman's correlations was wide (0.21-0.92; 16 studies). Inconsistencies between MDs, percentage agreement and correlations were common., Conclusion: Magnetic resonance imaging appears to slightly overestimate pathologic size, but measurement errors may be large enough to be clinically significant. Comparable performance by US was observed, but agreement with pathology was poorer for mammography and clinical examination. Percentage agreement can provide supplementary information to MDs and LOA, but Pearson's/Spearman's correlation does not provide evidence of agreement and should be avoided. Further comparisons of MRI and other tests using the recommended methods are warranted.

Background: It has been proposed that magnetic resonance imaging (MRI) be used to guide breast cancer surgery by differentiating residual tumor from pathologic complete response (pCR) after neoadjuvant chemotherapy. This meta-analysis examines MRI accuracy in detecting residual tumor, investigates variables potentially affecting MRI performance, and compares MRI with other tests., Methods: A systematic literature search was undertaken. Hierarchical summary receiver operating characteristic (HSROC) models were used to estimate (relative) diagnostic odds ratios ([R]DORs). Summary sensitivity (correct identification of residual tumor), specificity (correct identification of pCR), and areas under the SROC curves (AUCs) were derived. All statistical tests were two-sided., Results: Forty-four studies (2050 patients) were included. The overall AUC of MRI was 0.88. Accuracy was lower for "standard" pCR definitions (referent category) than "less clearly described" (RDOR = 2.41, 95% confidence interval [CI] = 1.11 to 5.23) or "near-pCR" definitions (RDOR = 2.60, 95% CI = 0.73 to 9.24; P = .03.) Corresponding AUCs were 0.83, 0.90, and 0.91. Specificity was higher when negative MRI was defined as contrast enhancement less than or equal to normal tissue (0.83, 95% CI = 0.64 to 0.93) vs no enhancement (0.54, 95% CI = 0.39 to 0.69; P = .02), with comparable sensitivity (0.83, 95% CI = 0.69 to 0.91; vs 0.87, 95% CI = 0.80 to 0.92; P = .45). MRI had higher accuracy than mammography (P = .02); there was only weak evidence that MRI had higher accuracy than clinical examination (P = .10). No difference in MRI and ultrasound accuracy was found (P = .15)., Conclusions: MRI accurately detects residual tumor after neoadjuvant chemotherapy. Accuracy was lower when pCR was more rigorously defined, and specificity was lower when test negativity thresholds were more stringent; these definitions require standardization. MRI is more accurate than mammography; however, studies comparing MRI and ultrasound are required.

Background: Pathologic complete response (pCR) is a surrogate end-point for prognosis in neoadjuvant chemotherapy (NAC) for breast cancer. We aimed to report summary estimates of the proportion of subjects achieving pCR (pCR%) by tumour subtype, and to determine whether subtype was independently associated with pCR, in a study-level meta-analysis., Methods: We systematically identified NAC studies reporting pCR data according to tumour subtype, using predefined eligibility criteria. Descriptive, qualitative and quantitative data were extracted. Random effects logistic meta-regression examined whether pCR% was associated with subtype, defined using three categories for model 1 [hormone receptor positive (HR+/HER2-), HER2 positive (HER2+), triple negative (ER-/PR-/HER2-)] and 4 categories for model 2 [HER2+ further classified as HER2+/HR+ and HER2+/HR-]. Subtype-specific odds ratios (OR) were calculated and were adjusted for covariates associated with pCR in our data., Results: In model 1, based on 11,695 subjects from 30 eligible studies, overall pooled pCR% was 18.9% (16.6-21.5%), and in model 2 (20 studies, 8095 subjects) pooled pCR% was 18.5% (16.2-21.1%); tumour subtype was associated with pCR% (P<0.0001) in both models. Subtype-specific pCR% (model 2) was: 8.3% (6.7-10.2%) in HR+/HER2- [OR 1/referent], 18.7% (15.0-23.1%) in HER2+/HR+ [OR 2.6], 38.9% (33.2-44.9%) in HER2+/HR- [OR 7.1] and 31.1% (26.5-36.1%) in triple negative [OR 5.0]; pCR% was significantly higher for the HER2+/HR- compared with the triple negative subtype, however pCR% was very similar for these subtypes (and OR=5.0 both subtypes) when studies using HER2-directed therapy with NAC were excluded from the model. Neither sensitivity analysis (excluding unknown subtypes), nor adjustment for associated covariates, substantially altered our findings., Interpretation: This meta-analysis provides evidence of an independent association between breast cancer subtype and pCR; odds of pCR were highest for the triple negative and HER2+/HR- subtypes, with evidence of an influential effect on achieving pCR in the latter subtype through inclusion of HER2-directed therapy with NAC., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Magnetic resonance imaging (MRI) has been proposed to have a role in predicting final pathologic response when undertaken early during neoadjuvant chemotherapy (NAC) in breast cancer. This paper examines the evidence for MRI's accuracy in early response prediction. A systematic literature search (to February 2011) was performed to identify studies reporting the accuracy of MRI during NAC in predicting pathologic response, including searches of MEDLINE, PREMEDLINE, EMBASE, and Cochrane databases. 13 studies were eligible (total 605 subjects, range 16-188). Dynamic contrast-enhanced (DCE) MRI was typically performed after 1-2 cycles of anthracycline-based or anthracycline/taxane-based NAC, and compared to a pre-NAC baseline scan. MRI parameters measured included changes in uni- or bidimensional tumour size, three-dimensional volume, quantitative dynamic contrast measurements (volume transfer constant [Ktrans], exchange rate constant [k(ep)], early contrast uptake [ECU]), and descriptive patterns of tumour reduction. Thresholds for identifying response varied across studies. Definitions of response included pathologic complete response (pCR), near-pCR, and residual tumour with evidence of NAC effect (range of response 0-58%). Heterogeneity across MRI parameters and the outcome definition precluded statistical meta-analysis. Based on descriptive presentation of the data, sensitivity/specificity pairs for prediction of pathologic response were highest in studies measuring reductions in Ktrans (near-pCR), ECU (pCR, but not near-pCR) and tumour volume (pCR or near-pCR), at high thresholds (typically >50%); lower sensitivity/specificity pairs were evident in studies measuring reductions in uni- or bidimensional tumour size. However, limitations in study methodology and data reporting preclude definitive conclusions. Methods proposed to address these limitations include: statistical comparison between MRI parameters, and MRI vs other tests (particularly ultrasound and clinical examination); standardising MRI thresholds and pCR definitions; and reporting changes in NAC based on test results. Further studies adopting these methods are warranted., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Objectives: To estimate the incidence of metastatic breast cancer (MBC) in Australian women with an initial diagnosis of non-metastatic breast cancer., Design, Setting and Participants: A population-based cohort study of all women with non-metastatic breast cancer registered on the New South Wales Central Cancer Register (CCR) in 2001 and 2002 who received care in a NSW hospital., Main Outcome Measures: 5-year cumulative incidence of MBC; prognostic factors for MBC., Results: MBC was recorded within 5 years in 218 of 4137 women with localised node-negative disease (5-year cumulative incidence, 5.3%; 95% CI, 4.6%-6.0%); and 455 of 2507 women with regional disease (5-year cumulative incidence, 18.1%; 95% CI, 16.7%-19.7%). The hazard rate for developing MBC was highest in the second year after the initial diagnosis of breast cancer. Determinants of increased risk of MBC were regional disease at diagnosis, age less than 50 years and living in an area of lower socio-economic status., Conclusions: Our Australian population-based estimates are valuable when communicating average MBC risks to patients and planning clinical services and trials. Women with node-negative disease have a low risk of developing MBC, consistent with outcomes of adjuvant clinical trials. Regional disease at diagnosis remains an important prognostic factor.