BackgroundCanAssist-Breast is an immunohistochemistry based test that predicts risk of distant recurrence in early-stage hormone receptor positive breast cancer patients within first five years of diagnosis. Immunohistochemistry gradings for 5 biomarkers (CD44, ABCC4, ABCC11, N-Cadherin and pan-Cadherins) and 3 clinical parameters (tumor size, tumor grade and node status) of 298 patient cohort were used to develop a machine learning based statistical algorithm. The algorithm generates a risk score based on which patients are stratified into two groups, low- or high-risk for recurrence. The aim of the current study is to demonstrate the analytical performance with respect to repeatability and reproducibility of CanAssist-Breast.MethodsAll potential sources of variation in CanAssist-Breast testing involving operator, run and observer that could affect the immunohistochemistry performance were tested using appropriate statistical analysis methods for each of the CanAssist-Breast biomarkers using a total 309 samples. The cumulative effect of these variations in the immunohistochemistry gradings on the generation of CanAssist-Breast risk score and risk category were also evaluated. Intra-class Correlation Coefficient, Bland Altman plots and pair-wise agreement were performed to establish concordance on IHC gradings, risk score and risk categorization respectively.ResultsCanAssist-Breast test exhibited high levels of concordance on immunohistochemistry gradings for all biomarkers with Intra-class Correlation Coefficient of ≥0.75 across all reproducibility and repeatability experiments. Bland-Altman plots demonstrated that agreement on risk scores between the comparators was within acceptable limits. We also observed > 90% agreement on risk categorization (low- or high-risk) across all variables tested.ConclusionsThe extensive analytical validation data for the CanAssist-Breast test, evaluating immunohistochemistry performance, risk score generation and risk categorization showed excellent agreement across variables, demonstrating that the test is robust.Electronic supplementary materialThe online version of this article (10.1186/s12885-019-5443-5) contains supplementary material, which is available to authorized users.

In the pre-vaccination era, diphtheria was a leading cause of childhood mortality. With the introduction of routine childhood immunization, paediatric care and improved hygiene status the disease has been almost completely eradicated in many developed countries. On the contrary developing countries, still account for 80-90% of the global burden. Retrospective analysis of 52 cases of diphtheria over a period of 12 years at a tertiary referral hospital was carried out. They were analyzed for mortality and morbidity trends, immunization status, microbiological confirmation rates and antidiphtheritic serum (ADS) administration. Incidence in those over 5 years was 59.61%. Only 11.54% cases were either partially or fully immunized. The case fatality rate was 36.53%. Culture was performed only in 17 cases whereas ADS was administered in only 16 cases. In conclusion, the occurrence of diphtheria even in those immunized highlights the flaws in the present immunization program. Poor immunization coverage, lack of ADS, antibiotic resistance are the main reasons for re-emergence of diphtheria.

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