Pre-operative Concomitant Radio-chemotherapy in Bulky Carcinoma of the Cervix: A Single Institution Study

Objective To evaluate the treatment results of patients (pts) with FIGO stage IB2, IIA, IIB cervical carcinoma (CC) treated with pre-operative radio-chemotherapy, followed by extended radical hysterectomy. Methods Retrospective study of 148 women treated to the Institut Curie for operable FIGO Stage IB2 to IIB, biopsy proved CC. Among them, 70 pts, median age 46 years, were treated using the same regimen associating primary radio-cisplatinum based chemotherapy, intracavitary LDR brachytherapy, followed by extended radical hysterectomy. Kaplan-Meier estimates were used to draw survival curves. Comparisons of survival distribution were assessed by the log-rank test. Results Complete histological local-regional response was obtained in 56% of the pts (n = 39). Residual macroscopic or microscopic disease in the cervix was observed in 28 pts (40%). All but one had in-situ microscopic residual CC. Lateral residual disease in the parametria was also present in 9 pts, all with residual CC. Pelvic lymph nodes were free from microscopic disease in 56 pts (80%). Eight of 55 (11%) radiological N0 patients had microscopic nodal involvement, as compared to 6/15 (40%) radiological N1 (p = 0.03). Seventeen pts (25%) had residual cervix disease but negative nodes. After median follow-up of 40 months (range, 8–141), 38/70 patients (54.1%) are still alive and free of disease, 6 (8.6%) alive with disease, and 11 (15.8%) patients were lost for follow-up but free of disease. In Conclusion The treatment of locally advanced CC needs a new multidisciplinary diagnostic and treatment approach using new therapeutic arms to improve the survival and treatment tolerance among women presenting this disease

Optimise not compromise : the importance of a multidisciplinary breast cancer patient pathway in the era of oncoplastic and reconstructive surgery

Modern breast cancer care is a complex multidisciplinary undertaking in which the integrated function of multiple constituent parts is critical, and where changes to one therapeutic component may profoundly influence the delivery and outcomes of another. Oncoplastic and reconstructive breast surgery has evolved in the era of longer survival rates for women with breast cancer and aims to enhance oncological and cosmetic outcomes. However, concurrently there has been an expansion in the indications for post-mastectomy radiation therapy (Abdulkarim et al., 2011; Early Breast Cancer Trialists' Collaborative Group (EBCTCG), 2014; Poortmans et al., 2015; Wang et al., 2011), the recognition of several biologically distinct breast cancer subtypes (Perou et al., 2000; Sorlie et al., 2001, 2003; Cheang et al., 2008, 2009; Sotiriou et al., 2003; Millar et al., 2011; Blows et al., 2010; Schnitt, 2010; Haque et al., 2012; Dai et al., 2015) and the development of recommendations for prophylactic surgery for high-risk women, including BRCA-mutation carriers (James et al., 2006; Domchek et al., 2010). Primary systemic therapy is increasingly utilised yet has varying efficacy depending on tumour biology (Cortazar et al., 2014). In this paper we review the evidence which informs the multidisciplinary team opinion in the era of oncoplastic and reconstructive breast surgery. We aim to describe an optimal multidisciplinary approach which balances competing risks of multimodal therapies to optimise oncological and cosmetic outcomes

The molecular subtype classification is a determinant of sentinel node positivity in early breast carcinoma.

INTRODUCTION: Several authors have underscored a strong relation between the molecular subtypes and the axillary status of breast cancer patients. The aim of our work was to decipher the interaction between this classification and the probability of a positive sentinel node biopsy. MATERIALS AND METHODS: Our dataset consisted of a total number of 2654 early-stage breast cancer patients. Patients treated at first by conservative breast surgery plus sentinel node biopsies were selected. A multivariate logistic regression model was trained and validated. Interaction covariate between ER and HER2 markers was a forced input of this model. The performance of the multivariate model in the training and the two validation sets was analyzed in terms of discrimination and calibration. Probability of axillary metastasis was detailed for each molecular subtype. RESULTS: The interaction covariate between ER and HER2 status was a stronger predictor (p = 0.0031) of positive sentinel node biopsy than the ER status by itself (p = 0.016). A multivariate model to determine the probability of sentinel node positivity was defined with the following variables; tumour size, lympho-vascular invasion, molecular subtypes and age at diagnosis. This model showed similar results in terms of discrimination (AUC = 0.72/0.73/0.72) and calibration (HL p = 0.28/0.05/0.11) in the training and validation sets. The interaction between molecular subtypes, tumour size and sentinel nodes status was approximated. DISCUSSION: We showed that biologically-driven analyses are able to build new models with higher performance in terms of breast cancer axillary status prediction. The molecular subtype classification strongly interacts with the axillary and distant metastasis process

Percentage of positive sentinel node.

<p>Percentage of positive sentinel node calculated for each 5 mm tumour size subclasses from 0 to 40 mm. Number of patient by tumour size subclasses are printed. The training and two validation datasets have been merged to determine these probability plots.</p

Number and percentage of lymph node negative breast cancer patients by molecular subgroup as determined by a combination of ER and <i>HER2</i> IHC markers. Review of literature.

<p>LNN; Nulber of Lymph Node Negative Patients. LN; Number of patients.</p

Nomogram to calculate the probability of sentinel node positivity in breast carcinoma.

<p>Nomogram to calculate the probability of sentinel node positivity in breast carcinoma. First: identify for each of the 4 variables the corresponding Beta value. Second, calculate the sum of the 4 Beta values. Third, report the Sum Beta Value to the Probability scale.</p

Clinical and pathological features of the training set and two validation sets.

<p>LVI: Lymphovascular Invasion. SN: Sentinel Node. No:Number. IHC: Immuno-Histochemistry. FISH: Fluorescent In Situ Hybridization.</p

Multivariate logistic regression model to predict the probability of axillary metastases.

<p>LVI: Lymphovascular Invasion. ERneg: Estrogen Receptor Negative. ERpos: Estrogen Receptor Positive. HER2neg: HER2 negative. Her2pos: HER2 positive. OR: Odds Ratio. CI: Confidence Interval. N: Number of patients</p

Clinical and pathological features of the sentinel node negative and positive tumours.

<p>LVI: Lymphovascular Invasion. SN: Sentinel Node. No:Number. IHC: Immuno-Histochemistry. FISH: Fluorescent In Situ Hybridization.</p