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Multimodality Imaging for Planning and Assessment in Radiation Therapy
Published in Siyong Kim, John Wong, Advanced and Emerging Technologies in Radiation Oncology Physics, 2018
Matthias Guckenberger, Geoffrey Hugo, Elisabeth Weiss
Cervix cancer is the fourth most common cancer in women and represents about 8% of all cancer diagnoses in women (http://www.wcrf.org/int/cancer-facts-figures/worldwide-data). Radiotherapy combined with chemotherapy (CRT) is the standard treatment approach for patients with locally advanced stage IB to stage IVA disease. These tumors are typically confined to the pelvis, including potential involvement of paraortic lymph nodes, but they are too advanced for surgery. The survival rate depends on the extent of the disease at the time of diagnosis. The 5-year overall survival rate in the United States is 68% for all tumor stages and 57% for locally advanced disease (http://www.cancer.net/cancer-types/cervical-cancer/statistics). Despite excellent pelvic control for early-stage disease, recurrence in the pelvis involving the primary tumor area and areas of direct tumor invasion in the parametria and vagina as well as pelvic lymph nodes have been frequent in locoregionally advanced tumors. In a large single institution report, 24% of all patients had locoregional recurrences following standard CRT (Beadle et al., 2010).
Assessment of Quercetin Isolated from Enicostemma Littorale Against Few Cancer Targets: An in Silico Approach
Published in A. K. Haghi, Ana Cristina Faria Ribeiro, Lionello Pogliani, Devrim Balköse, Francisco Torrens, Omari V. Mukbaniani, Applied Chemistry and Chemical Engineering, 2017
Prognosis and survival rate varies and it greatly depends on the cancer type and staging. With best treatment and dependent on staging, 5-year relative survival varies from 98 to 23% with an overall survival rate of 85% (Cancer World Report 2008). Worldwide, breast cancer comprises of 22.9% of all non-melanoma skin cancers in women. In 2008, breast cancer caused 458,503 deaths worldwide, 13.7% of cancer deaths in women alone which was 100 times more common than men, although males tend to have poorer outcomes due to delays in diagnosis. The first noticeable symptom of breast cancer is typically a lump that feels different from the rest of the breast tissue. More than 80% of breast cancer cases are discovered when the woman feels a lump.38 The earliest breast cancers are detected by a mammogram and lumps found in lymph nodes located in the armpits can also indicate breast cancer. Indications of breast cancer other than a lump may include changes in breast size or shape, skin dimpling, nipple inversion, or spontaneous single-nipple discharge.
The Clinical Development of Biosimilar Drugs
Published in Laszlo Endrenyi, Paul Jules Declerck, Shein-Chung Chow, Biosimilar Drug Product Development, 2017
Mark McCamish, Gillian Woollett, Sigrid Balser
Transitioning to oncology studies, primary endpoints in trials for regulatory approval are overwhelmingly focused on the overall survival of patients after treatment with a new agent. This is appropriate as one wants to understand whether the new treatment actually has an impact on the survival of patients. Measuring other parameters such as size of the tumor after treatment or overall response could reveal a difference in tumor mass that does not benefit the patient’s survival. Since trials looking at overall survival may take substantial time, some regulatory authorities, such as the FDA, came up with approaches for accelerated approval using progression free survival (PFS). Drugs approved using a primary endpoint of progression free survival are usually required to ultimately demonstrate a positive impact on overall survival.
Recent advances of polymer based nanosystems in cancer management
Published in Journal of Biomaterials Science, Polymer Edition, 2023
Chetan Janrao, Shivani Khopade, Akshay Bavaskar, Shyam Sudhakar Gomte, Tejas Girish Agnihotri, Aakanchha Jain
The majority of cancer cases are diagnosed when they are already progressed, metastasize, or are in advanced stages. Unfortunately, only 16% of cancer cases are detected before they turn malignant [212]. Molecular imaging (MI) has the advantage of allowing for the early diagnosis of a few malignant cells before they grow into solid tumors. It can quantitatively identify cellular events (biological processes) by applying novel probes that target certain diseased state biomarkers. Small animal imaging using nanostructure-based probes that target primary and metastatic cancer cells and tissues is important in the diagnosis. Fluorescent nanoparticles, such as organic dye-containing nanoparticles, quantum dots, and up-conversion nanoparticles, have been used in small animal imaging at the cellular level, which had an impact on cancer diagnosis and treatment [213]. Real-time visualization of in vivo cellular structure and function will help to understand the fundamental cause of the diseased situation in both animal species and humans. Functional level research on cells and tissues will increase overall survival and the effectiveness of cancer treatment. Entire body imaging offers non-invasive, quantitative, and comparatively safe outputs for the early detection and monitoring of human diseases.
Learning curve and factors influencing successful robot-assisted bilateral sentinel lymph node mapping in early-stage cervical cancer: an observational cohort study
Published in Expert Review of Medical Devices, 2023
Ilse G.T. Baeten, Jacob P. Hoogendam, Arthur J.A.T. Braat, Bart de Keizer, Cornelis G. Gerestein, Ronald P. Zweemer
Survival curves were estimated using Kaplan-Meier method and differences between groups were compared using log-rank test. Overall survival was defined as the time interval between diagnosis and death of any cause. Disease-free survival was defined as time interval between diagnosis and disease recurrence, detected clinically, by imaging, or histopathological biopsy. For the cumulative bilateral detection rate, the number of cases with bilateral detection was divided by the serial number of procedures performed.
Improving Recurrence Prediction Accuracy of Ovarian Cancer Using Multi-phase Feature Selection Methodology
Published in Applied Artificial Intelligence, 2021
S. Sujamol, E. R. Vimina, U. Krishnakumar
Ovarian Cancer (OC) seems to be a deadly disease that is now diagnosed more frequently. Cancer statistics in 2018, reported about 22,240 new cases and 14,070 deaths in the United States, 52,100 new cases with 22,500 deaths in China and even more cases in other countries (Siegel, Miller, and Jemal 2018). Due to the high recurrence rate, the overall survival is just 30% even after surgical resection and chemotherapy. American cancer society defines recurrence as the detection of cancer after treatment and after a certain time period usually one year within the same place where it originated or any other body part. In order to manifest suitable therapies for improved treatment outcomes, it is necessary to determine high recurrence risk patients in the early stage itself. Monitoring the clinical symptoms alone will not provide a guaranteed solution since 70% of OC patients experience recurrence (Diaz-Gil et al. 2016; Vistad et al. 2017). It is necessary to bring out those molecular level biomarkers acting behind recurrence prediction and overall survival. Analysis of gene expressions using microarrays is one of the commonly used methods for cancer biomarker detection. Gene alteration and protein structure prediction can be applied in many treatment therapies. Recently, the role of MiRNAs has been found in human biological processes including carcinogenesis, cellular, and embryonic development (Zhang et al. 2020). They have been widely used in cancer research due to their prominent role in gene regulation. These small noncoding RNAs hinders the protein translation process by targeting messenger RNAs (mRNAs) thereby affecting crucial organic processes, namely, proliferation of cells, hematopoiesis, apoptosis, and secretion of insulin within a human body. Since they have the capacity to regulate gene expression, MiRNAs are widely used in cancer research. MiRNA expression profiling was analyzed in many studies and found that these expression profiles are altered in different cancers like acute leukemia, lung cancer, Pan-Cancer, breast cancer, and glioblastoma (Li and Kowdley 2012). Many machine learning approaches have used gene profiling for cancer grade classification and recurrence prediction. But it has been scientifically proved that MiRNA profiling delivers more accurate results than gene profiling (Lu et al. 2005). MiRNA expression profiling reveals the molecular signature of different cancer types and hence they were used in many studies and found that they were associated with cancer progression as well as overall survival of cancer patients. So MiRNA expression analysis can highly contribute to recurrence prediction and survival analysis. Earlier studies reported that the expression of the miR-200 family is directly associated with recurrence (Koutsaki et al. 2017). Although there are many papers that discuss the application of machine learning techniques in recurrence prediction, early identification of OC recurrence is still in its dormant stage.