Coronavirus disease 2019 (COVID-19) is an infectious disease caused by a new virus that has never been identified in humans before. COVID-19 caused at the time of writing of this article, 2.5 million cases of infections in 193 countries with 165,000 deaths, including two-third in Europe. In this context, Oncology Departments of the affected countries had to adapt quickly their health system care and establish new organizations and priorities. Thus, numerous recommendations and therapeutic options have been reported to optimize therapy delivery to patients with chronic disease and cancer. Obviously, while these cancer care recommendations are immediately applicable in Europe, they may not be applicable in certain emerging and low- and middle-income countries (LMICs). In this review, we aimed to summarize these international guidelines in accordance with cancer types, making a synthesis for daily practice to protect patients, staff and tailor anti-cancer therapy delivery taking into account patients/tumour criteria and tools availability. Thus, we will discuss their applicability in the LMICs with different organizations, limited means and different constraints.

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BackgroundA strong correlation between breast cancer (BC) molecular subtypes and axillary status has been shown. It would be useful to predict the probability of lymph node (LN) positivity. Objective: To develop the performance of multivariable models to predict LN metastases, including nomograms derived from logistic regression with clinical, pathologic variables provided by tumor surgical results or only by biopsy.MethodsA retrospective cohort was randomly divided into two separate patient sets: a training set and a validation set. In the training set, we used multivariable logistic regression techniques to build different predictive nomograms for the risk of developing LN metastases. The discrimination ability and calibration accuracy of the resulting nomograms were evaluated on the training and validation set.ResultsConsecutive sample of 12,572 early BC patients with sentinel node biopsies and no neoadjuvant therapy. In our predictive macro metastases LN model, the areas under curve (AUC) values were 0.780 and 0.717 respectively for pathologic and pre-operative model, with a good calibration, and results with validation data set were similar: AUC respectively of 0.796 and 0.725.Among the list of candidate’s regression variables, on the training set we identified age, tumor size, LVI, and molecular subtype as statistically significant factors for predicting the risk of LN metastases.ConclusionsSeveral nomograms were reported to predict risk of SLN involvement and NSN involvement. We propose a new calculation model to assess this risk of positive LN with similar performance which could be useful to choose management strategies, to avoid axillary LN staging or to propose ALND for patients with high level probability of major axillary LN involvement but also to propose immediate breast reconstruction when post mastectomy radiotherapy is not required for patients without LN macro metastasis.Electronic supplementary materialThe online version of this article (10.1186/s12885-018-5227-3) contains supplementary material, which is available to authorized users.

BackgroundWhen invasive components are discovered at mastectomy for vacuum-assisted biopsy (VAB)-diagnosed ductal carcinoma in situ (DCIS), the only option available is axillary lymph node dissection (ALND). The primary aim of this prospective multicenter trial was to determine the benefit of performing upfront sentinel lymph node (SLN) biopsy for these patients. The secondary aim was to determine DCIS factors associated with microinvasion or invasion.MethodsThe SLN procedure was performed during mastectomy, and for positive SLN an ALND was performed during the same intervention. A tissue microarray containing DCIS lesions from the mastectomy specimens was subsequently performed.ResultsFrom May 2008 to December 2010, 228 patients were enrolled from 14 French cancer centers, including 192 eligible patients with pure DCIS on VAB and successful SLN procedures. ALND was avoided for 51 [67 %; 95 % confidence interval (CI), 56–77 %] of all the patients who had microinvasive DCIS or DCIS associated with invasive carcinoma at mastectomy and a negative SLN. Of the 192 patients, 76 (39 %) with VAB-diagnosed DCIS were upgraded after mastectomy to micro (n = 20) or invasive disease (n = 56). The rate of positive SLN for patients with DCIS on VAB was 14 %. High nuclear grade of DCIS was associated with greater risk of microinvasion and invasion, and HER2-amplified DCIS was associated with greater risk of invasion.ConclusionsUnderestimation of invasive components is high when DCIS is diagnosed by VAB in patients undergoing mastectomy. Upfront SLN for patients with VAB-diagnosed extensive DCIS avoids unnecessary ALND for two-thirds of patients with micro or invasive disease on mastectomy.Electronic supplementary materialThe online version of this article (doi:10.1245/s10434-015-4476-5) contains supplementary material, which is available to authorized users.

In patients with no personal or first-degree family history of breast cancer, after complete or subtotal excision under radiology of the radiological lesion, and while excluding images fitting BI-RADS 5, annual monitoring may be offered as an alternative to surgical excision in view of the absence of underestimation found in our study.