Random effects models of tumour growth for investigating interval breast cancer.

In Nordic countries and across Europe, breast cancer screening participation is high. However, a significant number of breast cancer cases are still diagnosed due to symptoms between screening rounds, termed "interval cancers". Radiologists use the interval cancer proportion as a proxy for the screening false negative rate (ie, 1-sensitivity). Our objective is to enhance our understanding of interval cancers by applying continuous tumour growth models to data from a study involving incident invasive breast cancer cases. Building upon previous findings regarding stationary distributions of tumour size and growth rate distributions in non-screened populations, we develop an analytical expression for the proportion of interval breast cancer cases among regularly screened women. Our approach avoids relying on estimated background cancer rates. We make specific parametric assumptions concerning tumour growth and detection processes (screening or symptoms), but our framework easily accommodates alternative assumptions. We also show how our developed analytical expression for the proportion of interval breast cancers within a screened population can be incorporated into an approach for fitting tumour growth models to incident case data. We fit a model on 3493 cases diagnosed in Sweden between 2001 and 2008. Our methodology allows us to estimate the distribution of tumour sizes at the most recent screening for interval cancers. Importantly, we find that our model-based expected incidence of interval breast cancers aligns closely with observed patterns in our study and in a large Nordic screening cohort. Finally, we evaluate the association between screening interval length and the interval cancer proportion. Our analytical expression represents a useful tool for gaining insights into the performance of population-based breast cancer screening programs.

A Rough Colony Morphology of Mycobacterium abscessus Is Associated With Cavitary Pulmonary Disease and Poor Clinical Outcome.

BACKGROUND: The Mycobacterium abscessus complex (MABC) is a difficult to treat mycobacterium with two distinct morphologies: smooth and rough. As the clinical implications are unclear, we explored the morphology of MABC in relation to disease and outcome. METHODS: We performed a retrospective multicenter cohort study including patients with confirmed MABC in Sweden, 2009-2020, with treatment outcome as the primary outcome. MABC colony morphology was determined by light microscopy on Middlebrook 7H10 agar plates. RESULTS: Of the 71 MABC isolates, a defined morphology could be determined for 63 isolates, of which 40 were smooth (56%) and 23 were rough (32%). Immunosuppression, pulmonary disease, and cavitary lesion on chest radiographs were significantly associated with a rough isolate morphology. Participants with smooth isolates had more favorable treatment outcomes (12/14, 86%) compared to those with rough isolates (3/10, 30%). In an age-adjusted logistic regression, rough morphology of MABC was associated to lower odds of clinical cure compared to smooth morphology (adjusted odds ratio, 0.12; P = .049). CONCLUSIONS: Study participants with rough MABC colony morphology of isolates had a worse clinical outcome compared to those with smooth isolates. The biological mechanisms should be further characterized and colony morphology of MABC taken into account during clinical management.