The Challenges of Data Access for Historical Clinical Trials: A user experience

Many trials from yesteryear looked at the benefit of treatment A v treatment B in terms of recurrence and survival data only. With the advent of new research methods available such as whole genome sequencing, digital image analysis, Nanostring technologies, there is a burgeoning trend towards revisiting these older cohorts to collect tissue samples and update the follow-up data. The idea of applying modern research techniques to historic tissue cohorts with 30 years of follow-up data is attractive to commercial investors who are trying to validate new personalised medicine approaches to breast cancer treatments. Applying new methods to patient samples from long ago combined with a wealth of long term follow up is a dream research project. However it is not without several hurdles to overcome. Patient consent was gathered in a more lax way back in the early 1990’s so although patients consented to enter a trial, the process would not have been as rigorously documented as it is today. This means accessing these patients data records causes issue as we do not have ‘explicit informed consent’ to do so. We could go back to patients and re-consent them but this brings its own issues. How do we locate these patients to get permission to access their patient records without accessing the patient records to find out if they are still alive or are mentally competent to be re-consented? What data do you require from the patient records? The date of death and /or relapse? Or more specific data such as tumour grade, patient age at diagnosis, surgery or death? Where will the data be stored and who will have access to such data? This is the biggest hurdle we have faced as with overseas funders unable to perform their own analysis on their own sequencing data as the patient derived data must not leave the UK/EU. With the introduction of the Patient Benefit and Privacy Panel in 2016 and the introduction of the new GDPR regulations in May 2018 the access and use of data seems to be getting tighter yet the opportunities to use it keep expanding. Finding the correct balance to satisfy the regulators is key. A video of this presentation can be viewed at https://media.ed.ac.uk/media/0_z6dtx4z

Evaluation of multiple transcriptomic gene risk signatures in male breast cancer

Marcadors pronòstics; Biomarcadors tumoralsMarcadores pronósticos; Biomarcadores tumoralesPrognostic markers; Tumour biomarkersMale breast cancer (BCa) is a rare disease accounting for less than 1% of all breast cancers and 1% of all cancers in males. The clinical management is largely extrapolated from female BCa. Several multigene assays are increasingly used to guide clinical treatment decisions in female BCa, however, there are limited data on the utility of these tests in male BCa. Here we present the gene expression results of 381 M0, ER+ve, HER2-ve male BCa patients enrolled in the Part 1 (retrospective analysis) of the International Male Breast Cancer Program. Using a custom NanoString™ panel comprised of the genes from the commercial risk tests Prosigna®, OncotypeDX®, and MammaPrint®, risk scores and intrinsic subtyping data were generated to recapitulate the commercial tests as described by us previously. We also examined the prognostic value of other risk scores such as the Genomic Grade Index (GGI), IHC4-mRNA and our prognostic 95-gene signature. In this sample set of male BCa, we demonstrated prognostic utility on univariate analysis. Across all signatures, patients whose samples were identified as low-risk experienced better outcomes than intermediate-risk, with those classed as high risk experiencing the poorest outcomes. As seen with female BCa, the concordance between tests was poor, with C-index values ranging from 40.3% to 78.2% and Kappa values ranging from 0.17 to 0.58. To our knowledge, this is the largest study of male breast cancers assayed to generate risk scores of the current commercial and academic risk tests demonstrating comparable clinical utility to female BCa.This work has been funded by the Breast Cancer Research Foundation (BCRF) with additional funding provided by the Government of Ontario to the Ontario Institute of Cancer Research (OICR). This work was funded by the Breast Cancer Research Foundation (BCRF), the Susan G. Komen for the Cure Foundation and the Ontario Institute of Cancer Research (OICR). Funding for OICR is provided by the Government of Ontario

Computational approaches to support comparative analysis of multiparametric tests: Modelling versus Training.

Multiparametric assays for risk stratification are widely used in the management of breast cancer, with applications being developed for a number of other cancer settings. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. There is an increasing need for robust methods to support cost effective comparisons of test performance in multiple settings. The derivation of similar risk classifications using genes comprising the following multi-parametric tests Oncotype DX® (Genomic Health.), Prosigna™ (NanoString Technologies, Inc.), MammaPrint® (Agendia Inc.) was performed using different computational approaches. Results were compared to the actual test results. Two widely used approaches were applied, firstly computational "modelling" of test results using published algorithms and secondly a "training" approach which used reference results from the commercially supplied tests. We demonstrate the potential for errors to arise when using a "modelling" approach without reference to real world test results. Simultaneously we show that a "training" approach can provide a highly cost-effective solution to the development of real-world comparisons between different multigene signatures. Comparisons between existing multiparametric tests is challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. We present an approach, modelled in breast cancer, which can provide health care providers and researchers with the potential to perform robust and meaningful comparisons between multigene tests in a cost-effective manner. We demonstrate that whilst viable estimates of gene signatures can be derived from modelling approaches, in our study using a training approach allowed a close approximation to true signature results

Breast Cancer Index is a predictive biomarker of treatment benefit and outcome from extended tamoxifen therapy: final analysis of the Trans-aTTom study

PURPOSE: The Breast Cancer Index (BCI) HOXB13/IL17BR (H/I) ratio predicts benefit from extended endocrine therapy in hormone receptor–positive (HR(+)) early-stage breast cancer. Here, we report the final analysis of the Trans-aTTom study examining BCI (H/I)'s predictive performance. EXPERIMENTAL DESIGN: BCI results were available for 2,445 aTTom trial patients. The primary endpoint of recurrence-free interval (RFI) and secondary endpoints of disease-free interval (DFI) and disease-free survival (DFS) were examined using Cox proportional hazards regression and log-rank test. RESULTS: Final analysis of the overall study population (N = 2,445) did not show a significant improvement in RFI with extended tamoxifen [HR, 0.90; 95% confidence interval (CI), 0.69–1.16; P = 0.401]. Both the overall study population and N0 group were underpowered due to the low event rate in the N0 group. In a pre-planned analysis of the N(+) subset (N = 789), BCI (H/I)-High patients derived significant benefit from extended tamoxifen (9.7% absolute benefit: HR, 0.33; 95% CI, 0.14–0.75; P = 0.016), whereas BCI (H/I)-Low patients did not (−1.2% absolute benefit; HR, 1.11; 95% CI, 0.76–1.64; P = 0.581). A significant treatment-to-biomarker interaction was demonstrated on the basis of RFI, DFI, and DFS (P = 0.037, 0.040, and 0.025, respectively). BCI (H/I)-High patients remained predictive of benefit from extended tamoxifen in the N(+)/HER2(−) subgroup (9.4% absolute benefit: HR, 0.35; 95% CI, 0.15–0.81; P = 0.047). A three-way interaction evaluating BCI (H/I), treatment, and HER2 status was not statistically significant (P = 0.849). CONCLUSIONS: Novel findings demonstrate that BCI (H/I) significantly predicts benefit from extended tamoxifen in HR(+) N(+) patients with HER2(−) disease. Moreover, BCI (H/I) demonstrates significant treatment to biomarker interaction across survival outcomes

ARomatase Inhibition plus/minus Src-inhibitor SaracaTinib (AZD0530) in Advanced breast CAncer Therapy (ARISTACAT): a randomised phase II study

PURPOSE: The development of oestrogen resistance is a major challenge in managing hormone-sensitive metastatic breast cancer. Saracatinib (AZD0530), an oral Src kinase inhibitor, prevents oestrogen resistance in animal models and reduces osteoclast activity. We aimed to evaluate the efficacy of saracatinib addition to aromatase inhibitors (AI) in patients with hormone receptor-positive metastatic breast cancer. METHODS: This phase II multicentre double-blinded randomised trial allocated post-menopausal women to AI with either saracatinib or placebo (1:1 ratio). Patients were stratified into an "AI-sensitive/naïve" group who received anastrozole and "prior-AI" group who received exemestane. Primary endpoint was progression-free survival (PFS). Secondary endpoints included overall survival (OS), objective response rate (ORR) and toxicity. RESULTS: 140 patients were randomised from 20 UK centres to saracatinib/AI (n = 69) or placebo/AI (n = 71). Saracatinib was not associated with an improved PFS (3.7 months v. 5.6 months placebo/AI) and did not reduce likelihood of bony progression. There was no benefit in OS or ORR. Effects were consistent in "AI-sensitive/naive" and "prior-AI" sub-groups. Saracatinib was well tolerated with dose reductions in 16% and the main side effects were gastrointestinal, hypophosphatemia and rash. CONCLUSION: Saracatinib did not improve outcomes in post-menopausal women with metastatic breast cancer. There was no observed beneficial effect on bone metastases. CRUKE/11/023, ISRCTN23804370

Analytical validation of a standardised scoring protocol for Ki67 immunohistochemistry on breast cancer excision whole sections: an international multicentre collaboration

Aims The nuclear proliferation marker Ki67 assayed by immunohistochemistry has multiple potential uses in breast cancer, but an unacceptable level of interlaboratory variability has hampered its clinical utility. The International Ki67 in Breast Cancer Working Group has undertaken a systematic programme to determine whether Ki67 measurement can be analytically validated and standardised among laboratories. This study addresses whether acceptable scoring reproducibility can be achieved on excision whole sections. Methods and results Adjacent sections from 30 primary ER+ breast cancers were centrally stained for Ki67 and sections were circulated among 23 pathologists in 12 countries. All pathologists scored Ki67 by two methods: (i) global: four fields of 100 tumour cells each were selected to reflect observed heterogeneity in nuclear staining; (ii) hot-spot: the field with highest apparent Ki67 index was selected and up to 500 cells scored. The intraclass correlation coefficient (ICC) for the global method [confidence interval (CI) = 0.87; 95% CI = 0.799-0.93] marginally met the prespecified success criterion (lower 95% CI >= 0.8), while the ICC for the hot-spot method (0.83; 95% CI = 0.74-0.90) did not. Visually, interobserver concordance in location of selected hot-spots varies between cases. The median times for scoring were 9 and 6 min for global and hot-spot methods, respectively. Conclusions The global scoring method demonstrates adequate reproducibility to warrant next steps towards evaluation for technical and clinical validity in appropriate cohorts of cases. The time taken for scoring by either method is practical using counting software we are making publicly available. Establishment of external quality assessment schemes is likely to improve the reproducibility between laboratories further

Analytical validation of a standardized scoring protocol for Ki67: phase 3 of an international multicenter collaboration

Pathological analysis of the nuclear proliferation biomarker Ki67 has multiple potential roles in breast and other cancers. However, clinical utility of the immunohistochemical (IHC) assay for Ki67 immunohistochemistry has been hampered by unacceptable between-laboratory analytical variability. The International Ki67 Working Group has conducted a series of studies aiming to decrease this variability and improve the evaluation of Ki67. This study tries to assess whether acceptable performance can be achieved on prestained core-cut biopsies using a standardized scoring method. Sections from 30 primary ER+ breast cancer core biopsies were centrally stained for Ki67 and circulated among 22 laboratories in 11 countries. Each laboratory scored Ki67 using three methods: (1) global (4 fields of 100 cells each); (2) weighted global (same as global but weighted by estimated percentages of total area); and (3) hot-spot (single field of 500 cells). The intraclass correlation coefficient (ICC), a measure of interlaboratory agreement, for the unweighted global method (0.87; 95% credible interval (CI): 0.81–0.93) met the prespecified success criterion for scoring reproducibility, whereas that for the weighted global (0.87; 95% CI: 0.7999–0.93) and hot-spot methods (0.84; 95% CI: 0.77–0.92) marginally failed to do so. The unweighted global assessment of Ki67 IHC analysis on core biopsies met the prespecified criterion of success for scoring reproducibility. A few cases still showed large scoring discrepancies. Establishment of external quality assessment schemes is likely to improve the agreement between laboratories further. Additional evaluations are needed to assess staining variability and clinical validity in appropriate cohorts of samples

An Ai Chi-based aquatic group improves balance and reduces falls in community-dwelling adults: A pilot observational cohort study

<p><b><i>Background</i></b>: Falls are associated with morbidity, loss of independence, and mortality. While land-based group exercise and Tai Chi programs reduce the risk of falls, aquatic therapy may allow patients to complete balance exercises with less pain and fear of falling; however, limited data exist. <b><i>Objective</i></b>: The objective of the study was to pilot the implementation of an aquatic group based on Ai Chi principles (Aquabalance) and to evaluate the safety, intervention acceptability, and intervention effect sizes. <b><i>Design</i></b>: Pilot observational cohort study. <b><i>Methods</i></b>: Forty-two outpatients underwent a single 45-minute weekly group aquatic Ai Chi-based session for eight weeks (Aquabalance). Safety was monitored using organizational reporting systems. Patient attendance, satisfaction, and self-reported falls were also recorded. Balance measures included the Timed Up and Go (TUG) test, the Four Square Step Test (FSST), and the unilateral Step Tests. <b><i>Results</i></b>: Forty-two patients completed the program. It was feasible to deliver Aquabalance, as evidenced by the median (IQR) attendance rate of 8.0 (7.8, 8.0) out of 8. No adverse events occurred and participants reported high satisfaction levels. Improvements were noted on the TUG, 10-meter walk test, the Functional Reach Test, the FSST, and the unilateral step tests (<i>p</i> < 0.05). The proportion of patients defined as high falls risk reduced from 38% to 21%. The study was limited by its small sample size, single-center nature, and the absence of a control group. <b><i>Conclusions</i></b>: Aquabalance was safe, well-attended, and acceptable to participants. A randomized controlled assessor-blinded trial is required.</p

Discordance between Immunohistochemistry and Erb-B2 Receptor Tyrosine Kinase 2 mRNA to Determine Human Epidermal Growth Factor Receptor 2 Low Status for Breast Cancer

Novel human epidermal growth factor receptor 2 (HER2)-directed antibody-drug conjugates have demonstrated efficacy in HER2-low expressing breast cancers, which are currently defined as those with immunohistochemistry (IHC) scores of 1+ or 2+ with a negative in situ hybridization assay. However, current HER2 testing methods are designed to identify HER2-amplified tumors with high expression levels. The true definition of HER2-low expressing breast cancers remains controversial. Using quantitative molecular analysis of breast cancers based on RNA expression, the dynamic range of HER2 expression exceeds that detected by in situ IHC approaches. Erb-B2 receptor tyrosine kinase 2 (ERBB2) mRNA expression levels across IHC groups using patient samples derived from the Tamoxifen Exemestane Adjuvant Multicenter Trial were investigated. The standardized mean differences in ERBB2 mRNA scores in log base 2 are 0.47 (95% CI, 0.36–0.57), 0.58 (95% CI, 0.26–0.70), and 0.32 (95% CI, −0.12 to 0.75) when comparing IHC 0+ without staining versus IHC 0+ with some staining, IHC 0+ with some staining versus IHC 1+, and IHC 1+ versus IHC 2+/fluorescence in situ hybridization–negative, respectively. The results showed immunohistochemical methods have a comparatively limited dynamic range for measuring HER2 protein expression. The range of expression based on RNA abundance suggests a molecular method defining HER2-low cancers may better serve the treatment decision needs of this group. Indeed, the validity of RNA abundance to identify HER2-low cancers and predict treatment response needs to be further evaluated by prospective clinical trials