Michael Luke Marinovich

Meta-analysis of the association of breast cancer subtype and pathologic complete response to neoadjuvant chemotherapy

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.

Ductal Carcinoma in Situ at Core-Needle Biopsy: Meta-Analysis of Underestimation and Predictors of Invasive Breast Cancer

PURPOSE To perform a meta-analysis to report pooled estimates for underestimation of invasive breast cancer (where core-needle biopsy [CNB] shows ductal carcinoma in situ [DCIS] and excision histologic examination shows invasive breast cancer) and to identify preoperative variables that predict invasive breast cancer. MATERIALS AND METHODS Studies were identified by searching MEDLINE and were included if they provided data on DCIS underestimates (overall and according to preoperative variables). Study-specific and pooled percentages for DCIS underestimates were calculated. By using meta-regression (random effects logistic modeling) the association between each study-level preoperative variable and understaged invasive breast cancer was investigated. RESULTS Fifty-two studies that included 7350 cases of DCIS with findings at excision histologic examination as the reference standard met the eligibility criteria and were included. There were 1736 underestimates (invasive breast cancer at excision); the random-effects pooled estimate was 25.9% (95% confidence interval: 22.5%, 29.5%). Preoperative variables that showed significant univariate association with higher underestimation included the use of a 14-gauge automated device (vs 11-gauge vacuum-assisted biopsy, P = .006), high-grade lesion at CNB (vs non-high grade lesion, P < .001), lesion size larger than 20 mm at imaging (vs lesions ≤ 20 mm, P < .001), Breast Imaging Reporting and Data System (BI-RADS) score of 4 or 5 (vs BI-RADS score of 3, P for trend = .005), mammographic mass (vs calcification only, P < .001), and palpability (P < .001). CONCLUSION About one in four DCIS diagnoses at CNB represent understaged invasive breast cancer. Preoperative variables significantly associated with understaging include biopsy device and guidance method, size, grade, mammographic features, and palpability.

Early prediction of pathologic response to neoadjuvant therapy in breast cancer: Systematic review of the accuracy of MRI

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 MRIs 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.

Meta-analysis of agreement between MRI and pathologic breast tumour size after neoadjuvant chemotherapy.

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.

Accuracy of ultrasound for predicting pathologic response during neoadjuvant therapy for breast cancer

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.

Digital breast tomosynthesis (3D mammography) for breast cancer screening and for assessment of screen-recalled findings: review of the evidence

ABSTRACT 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.