Purpose We compared the efficacy and toxicity of neoadjuvant chemotherapy followed by radical surgery versus standard cisplatin-based chemoradiation in patients with locally advanced squamous cervical cancer. Patients and Methods This was a single-center, phase III, randomized controlled trial ( ClinicalTrials.gov identifier: NCT00193739). Eligible patients were between 18 and 65 years old and had stage IB2, IIA, or IIB squamous cervical cancer. They were randomly assigned, after stratification by stage, to receive either three cycles of neoadjuvant chemotherapy using paclitaxel and carboplatin once every 3 weeks followed by radical hysterectomy or standard radiotherapy with concomitant cisplatin once every week for 5 weeks. Patients in the neoadjuvant group received postoperative adjuvant radiation or concomitant chemotherapy and radiotherapy, if indicated. The primary end point was disease-free survival (DFS), defined as survival without relapse or death related to cancer, and secondary end points included overall survival and toxicity. Results Between September 2003 and February 2015, 635 patients were randomly assigned, of whom 633 (316 patients in the neoadjuvant chemotherapy plus surgery group and 317 patients in the concomitant chemoradiation group) were included in the final analysis, with a median follow-up time of 58.5 months. The 5-year DFS in the neoadjuvant chemotherapy plus surgery group was 69.3% compared with 76.7% in the concomitant chemoradiation group (hazard ratio, 1.38; 95% CI, 1.02 to 1.87; P = .038), whereas the corresponding 5-year OS rates were 75.4% and 74.7%, respectively (hazard ratio, 1.025; 95% CI, 0.752 to 1.398; P = .87). The delayed toxicities at 24 months or later after treatment completion in the neoadjuvant chemotherapy plus surgery group versus the concomitant chemoradiation group were rectal (2.2% v 3.5%, respectively), bladder (1.6% v 3.5%, respectively), and vaginal (12.0% v 25.6%, respectively). Conclusion Cisplatin-based concomitant chemoradiation resulted in superior DFS compared with neoadjuvant chemotherapy followed by radical surgery in locally advanced cervical cancer.
Cervix and Breast cancers are the most common cancers among women worldwide and extract a large toll in developing countries. In May 1998, supported by a grant from the NCI (US), the Tata Memorial Hospital, Mumbai, India, started a clusterrandomized, controlled, screening-trial for cervix and breast cancer using trained primary health workers to provide healtheducation, visual-inspection of cervix (with 4% acetic acid-VIA) and clinical breast examination (CBE) in the screening arm, and only health education in the control arm. Four rounds of screening at 2-year intervals will be followed by 8 years of monitoring for incidence and mortality from cervix and breast cancers. The methodology and interim results after three rounds of screening are presented here. Good randomization was achieved between the screening (n 5 75360) and control arms (n 5 76178). In the screening arm we see: High screening participation rates; Low attrition; Good compliance to diagnostic confirmation; Significant downstaging; Excellent treatment completion rate; Improving case fatality ratios. The ever-screened and never-screened participants in the screening arm show significant differences with reference to the variables religion, language, age, education, occupation, income and health-seeking behavior for gynecological and breast-related complaints. During the same period, in the control arm we see excellent participation rate for health education; Low attrition and a good number of symptomatic referrals for both cervix and breast.Of the estimated 470,000 new cases of cervix cancer diagnosed each year worldwide, 80% occur in developing countries and around 27% occur in India from where 126,000 new cases are diagnosed annually and over 71,000 deaths because of cervix cancer are reported each year.1,2 Nearly 70% of cervix cancer patients in India present at stages III and IV.3 Around 20% of women who develop cervix cancer die within the first year of diagnosis and the 5-year relative survival rate is 50%. 4 Breast cancer is the most common cancer among women worldwide and is also the leading cause of cancer deaths in women. Breast cancer is responsible for an estimated 189,000 and 184,000 deaths in developed and developing countries respectively thus accounting for 16% and 12% of all cancer deaths in women. Although the age-standardized incidence of breast cancer is generally lower in developing countries than in developed countries (23.1 vs. 63.2 per 100,000 women), incidence rates are seen to vary widely between and within countries. Breast cancer is already more common than cervix cancer in a number of developing countries.5 Data from developing countries suggests that age-standardized incidence rates of breast cancer are rising rapidly in low-incidence regions such as Africa and Asia. 6 There are no organized screening programmes for cervix and breast cancers in India. Cervix Cytology and Mammography based screening programmes are difficult to organize in India because of issues related to absence of trained manpower, infrastructu...
Glioblastoma is a WHO grade IV brain tumor, which leads to poor overall survival (OS) of patients. For precise surgical and treatment planning, OS prediction of glioblastoma (GBM) patients is highly desired by clinicians and oncologists. Radiomic research attempts at predicting disease prognosis, thus providing beneficial information for personalized treatment from a variety of imaging features extracted from multiple MR images. In this study, first-order, intensity-based volume and shape-based and textural radiomic features are extracted from fluid-attenuated inversion recovery (FLAIR) and T1ce MRI data. The region of interest is further decomposed with stationary wavelet transform with low-pass and high-pass filtering. Further, radiomic features are extracted on these decomposed images, which helped in acquiring the directional information. The efficiency of the proposed algorithm is evaluated on Brain Tumor Segmentation (BraTS) challenge training, validation, and test datasets. The proposed approach achieved 0.695, 0.571, and 0.558 on BraTS training, validation, and test datasets. The proposed approach secured the third position in BraTS 2018 challenge for the OS prediction task.
Conventional magnetic resonance (MR) imaging has an established role in gynecologic imaging. However, increasing clinical demand for improved lesion characterization and disease mapping to optimize patient management has resulted in the incorporation of newer sequences, such as diffusion-weighted (DW) imaging, into routine protocols for pelvic MR imaging. DW imaging provides functional information about the microenvironment of water in tissues, hence augmenting the morphologic information derived from conventional MR images. It can depict shifts of water from extracellular to intracellular compartments, altered cell membrane permeability, disruption of cell membrane depolarization, and increased cellular density. Such changes may be associated with tumors. DW imaging has emerged as an important cancer biomarker and takes the role of the radiologist from the level of mere macroscopic diagnosis to more active participation in determining patient prognosis and management through a better understanding of the tumor microenvironment. With the growing acknowledgment of DW imaging as a pivotal tool in the radiologist's armamentarium, radiologists must be familiar with the appearances of various gynecologic tumors at DW imaging and understand the implications of this sequence for improving diagnostic accuracy and predicting and monitoring treatment response. Although positron emission tomography/computed tomography is extremely useful for detecting tumor recurrence in cervical and ovarian carcinomas, it has a limited specificity in the immediate posttreatment setting. DW imaging may aid in detection of residual or recurrent tumors in such situations. DW imaging is a potentially useful adjunct to conventional MR imaging for evaluation of gynecologic tumors, thus improving overall diagnostic accuracy, tumor staging, prediction of response to therapy, and treatment follow-up.
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