An independent, not-for-profit consortium to accelerate research, and improve treatment for patients affected with the most commonly-diagnosed cancers in Asia by generating a genomic data resource for the most prevalent cancers in Asia. ACRG is focusing its initial efforts on Asian liver, gastric and lung cancers. Goals * Generate comprehensive genomics data sets for Asia-prevalent cancers * Conduct all research under good clinical practices and in accordance with local laws * Uncover key mutations and pathways for developing targeted therapies * Discover molecular tumor classifiers for patient stratification * Discover prognostic markers to identify high-risk patients * Freely share resulting raw data with scientific community to empower researchers globally and enable development of new diagnostics and medicines * Publish data analysis results jointly in prominent scientific journals Over the next two years, Lilly, Merck and Pfizer have committed to create an extensive pharmacogenomic cancer database that will be composed of data from approximately 2,000 tissue samples from patients with lung and gastric cancer that will be made publicly available to researchers and, over time, further populated with clinical data from a longitudinal analysis of patients. Comparison of the contrasting genomic signatures of these cancers could inform new approaches to treatment. Lilly has assumed responsibility for ultimately providing the data to the research public through an open-source concept managed by Lilly''''s Singapore research site. Moreover, Lilly, Merck and Pfizer will each provide technical and intellectual expertise. One dataset can be found at http://gigadb.org/dataset/100034

Users can access data about cancer statistics in the United States including but not limited to searches by type of cancer and race, sex, ethnicity, age at diagnosis, and age at death. Background Surveillance Epidemiology and End Results (SEER) database’s mission is to provide information on cancer statistics to help reduce the burden of disease in the U.S. population. The SEER database is a project to the National Cancer Institute. The SEER database collects information on incidence, prevalence, and survival from specific geographic areas representing 28 percent of the United States population. User functionality Users can access a variety of reso urces. Cancer Stat Fact Sheets allow users to look at summaries of statistics by major cancer type. Cancer Statistic Reviews are available from 1975-2008 in table format. Users are also able to build their own tables and graphs using Fast Stats. The Cancer Query system provides more flexibility and a larger set of cancer statistics than F ast Stats but requires more input from the user. State Cancer Profiles include dynamic maps and graphs enabling the investigation of cancer trends at the county, state, and national levels. SEER research data files and SEER*Stat software are available to download through your Internet connection (SEER*Stat’s client-server mode) or via discs shipped directly to you. A signed data agreement form is required to access the SEER data Data Notes Data is available in different formats depending on which type of data is accessed. Some data is available in table, PDF, and html formats. Detailed information about the data is available under “Data Documentation and Variable Recodes”.

BackgroundThe use of alternative modeling techniques for predicting patient survival is complicated by the fact that some alternative techniques cannot readily deal with censoring, which is essential for analyzing survival data. In the current study, we aimed to demonstrate that pseudo values enable statistically appropriate analyses of survival outcomes when used in seven alternative modeling techniques.MethodsIn this case study, we analyzed survival of 1282 Dutch patients with newly diagnosed Head and Neck Squamous Cell Carcinoma (HNSCC) with conventional Kaplan-Meier and Cox regression analysis. We subsequently calculated pseudo values to reflect the individual survival patterns. We used these pseudo values to compare recursive partitioning (RPART), neural nets (NNET), logistic regression (LR) general linear models (GLM) and three variants of support vector machines (SVM) with respect to dichotomous 60-month survival, and continuous pseudo values at 60 months or estimated survival time. We used the area under the ROC curve (AUC) and the root of the mean squared error (RMSE) to compare the performance of these models using bootstrap validation.ResultsOf a total of 1282 patients, 986 patients died during a median follow-up of 66 months (60-month survival: 52% [95% CI: 50%−55%]). The LR model had the highest optimism corrected AUC (0.791) to predict 60-month survival, followed by the SVM model with a linear kernel (AUC 0.787). The GLM model had the smallest optimism corrected RMSE when continuous pseudo values were considered for 60-month survival or the estimated survival time followed by SVM models with a linear kernel. The estimated importance of predictors varied substantially by the specific aspect of survival studied and modeling technique used.ConclusionsThe use of pseudo values makes it readily possible to apply alternative modeling techniques to survival problems, to compare their performance and to search further for promising alternative modeling techniques to analyze survival time.

In recent decades, there has been a deluge in the large-scale production of anticancer agents, primarily due to advances in genomic technologies enabling precise targeting of oncogenic pathways involved in disease progression. This initiated a paradigm shift in cancer research and therapeutics based on the ability to study molecular changes throughout the genome. It provided a unique opportunity in the field of translational cancer research and have led to the concept of precision medicine in cancer therapy, raising hopes of developing better diagnostic and therapeutic means for the management of cancer. The purpose of this article is to briefly review the tools and techniques involved in precision oncology research and their applications in the field of cancer treatment.

Background: A cancer patient's quality of life (QoL) is the perception of their physical, functional, psychological, and social well-being as well as their mental and emotional state. QoL is one of the most important factors to consider when a person is being treated for cancer and during follow-up. The present study aimed to understand the status of QoL of cancer patients and determine the factors affecting it.

Methods: This cross-sectional study was conducted among 210 cancer patients attending the oncology unit of a medical college, within a 4-month consecutive time period in 2022. Data were collected by using the Bengali version of the European Organization for Research and Treatment of Cancer questionnaire.

Results: The present study reported a high number of female cancer patients (67.6%). Breast cancer was more common among females (31.43%) while lung and upper respiratory tract cancer was among males (19.05). Most of the patients in the present study were diagnosed with cancer in the past year (86.19%). The functional scales' overall mean scores varied from 54.92 for physical functioning to 38.89 for social functioning. The highest symptom scale score was for financial issues (63.02), while the lowest was for diarrhea (33.01). The overall QoL of cancer patients in the present study was 47.98 which was 45.71 for males and 49.10 for females respectively.

Conclusion: The overall QoL was poor in cancer patients in the present study compared to the developed countries. There was a low score for QoL for social and emotional function. Financial difficulty was the primary reason behind low QoL in the symptom scale. If the government supports cancer patients by providing subsidies for treatment and health insurance policies, cancer patients will benefit and QoL will improve.

Initiative to advance oncology research by enabling collaborative sharing of historical oncology clinical trial data through a universal platform (database). The initiative aims to network all stakeholders in the cancer community researchers, industry, academia, advocacy, and other organizations to share insights and collaborate on issues that could not be solved individually. To do this, they have made efforts to address issues of data privacy, security, intellectual property, resources, and incentives as part of its effort to maximize participation. Data contributions include control arms of clinical trials, and the platform uses data-security precautions and analytics to pool multiple studies associated with the same diagnosis in a manner that seeks to protect the privacy of patients and the security of the data contributed.

The dataset contains information of 213 cancer patients undergoing clinical or surgical treatment characterized on sociodemographic and clinical data as well as data from the Care Transition Measure (CTM 15-Brazil). Data collection was carried out 7 to 30 days after their discharge from hospital from June to August 2019. Understanding these data can contribute to improving quality of care transitions and avoiding hospital readmissions. To this end, this dataset contains a broad array of variables:

*gender

*age group

*place of residence

*race

*marital status

*schooling

*paid work activity

*type of treatment

*cancer staging

*metastasis

*comorbidities

*main complaint

*continue use medication

*diagnosis

*cancer type

*diagnostic year

*oncology treatment

*first hospitalization

*readmission in the last 30 days

*number of hospitalizations in the last 30 days

*readmission in the last 6 months

*number of hospitalizations in the last 6 months

*readmission in the last year

*number of hospitalizations in the last year

*questions 1-15 from CTM 15-Brazil

The data are presented as a single Excel XLSX file: cancer patient´s care transitions dataset.xlsx.

The analyses of the present dataset have the potential to generate hospital readmission prevention strategies to be implemented by the hospital team. Researchers who are interested in CTs of cancer patients can extensively explore the variables described here.

The project from which these data were extracted was approved by the institution’s research ethics committee (approval n. 3.266.259/2019) at Associação Hospital de Caridade Ijuí, Rio Grande do Sul, Brazil.

Cancer funding by the NIH was around 7.6 billion U.S. dollars in fiscal year 2023. This statistic shows the actual cancer funding by the National Institutes for Health (NIH) from FY 2013 to FY 2023 and estimates for FYs 2024 and 2025.

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Cancer Registry Software Market Size 2024-2028

The cancer registry software market size is forecast to increase by USD 97.1 million at a CAGR of 12.75% between 2023 and 2028.

The growing prevalence of cancer cases is the key driver of the cancer registry software market. CDC is a key player, specializing in providing advanced cancer registry software solutions, including Registry Plus. These systems facilitate accurate and efficient data management for healthcare organizations, enabling effective tracking, analysis, and reporting of cancer patient information as well as supporting cancer immunotherapy and cancer diagnostics. By supporting improved patient care and research outcomes, CDC's solutions are essential in addressing the increasing demand for comprehensive cancer data management. 
Additionally, data privacy and security concerns are driving the market, as healthcare organizations prioritize protecting sensitive patient information. These trends are shaping the market, which is expected to continue its growth trajectory In the coming years.

What will be the Size of the Cancer Registry Software Market During the Forecast Period?

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The market is experiencing significant growth due to the increasing incidence of cancer and the need for efficient and accurate data management In the healthcare industry. With the adoption of Electronic Health Records (EHRs) and the shift towards evidence-based medicine, cancer registry software solutions have become essential tools for medical professionals to track cancer treatment, therapeutics, and patient outcomes. 
These solutions enable the collection and analysis of data on cancer prevalence, diagnostics, and specific area-focused cancer incidence. They provide valuable insights into cancer-specific outcomes, including chemotherapy, surgery, supportive treatments, and post-endoscopic resection. Furthermore, regulatory guidance documents mandate the use of cancer registry software to ensure compliance with healthcare standards and reduce healthcare costs.
Medical professionals rely on these software solutions to improve patient care and support the ongoing research and development of new cancer treatments.

How is this Cancer Registry Software Industry segmented and which is the largest segment?

The cancer registry software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  Government and third party
  Pharma biotech and medical device companies
  Hospitals and medical practice
  Private payers
  Research institutes


Type

  Stand-alone software
  Integrated software


Deployment

  On-premise
  Cloud


Component

  Commercial
  Public


Geography

  North America

    Canada
    US


  Europe

    Germany
    Italy


  Asia

    China


  Rest of World (ROW)

By End-user Insights

The government and third party segment is estimated to witness significant growth during the forecast period. Cancer registry software plays a pivotal role in managing data related to cancer cases for government hospitals and third-party agencies. This software facilitates the collection, management, and analysis of data on cancer incidence, prevalence, and mortality rates. This information is essential for public health planning, resource allocation, and policy development. By identifying trends and patterns, governments and agencies can target high-risk populations, address geographic disparities, and recognize emerging cancer types. Cancer registry software enhances the quality of cancer care by enabling the evaluation of treatment practices against clinical guidelines and benchmarking outcomes against standards. The software supports seamless data integration and interoperability with healthcare systems, ensuring coordinated care for cancer patients.

Medical professionals and patients alike benefit from improved cancer care through evidence-based medicine, cancer-specific outcomes, and research institutes. Software solutions cater to various cancer types, including lung cancer, and support cancer staging, treatment, disease management, diagnostics, chemo, surgery, and supportive therapies. These solutions integrate with electronic health records (EHR), enabling secure data storage and access to essential health information. Data security and security protocols are prioritized to protect patient privacy and prevent medical identity theft. Cancer registry software supports population health management, healthcare cost containment, and chronic disease management. It aligns with healthcare quality goals and streamlines hospital workflows, making it an essential tool for oncology departments, clinics, hospitals, medical practices, pharmaceutical, biotech, and medical de

The Oncology Information Systems (OIS) market is experiencing robust growth, projected to reach $3.0 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 6.7% from 2025 to 2033. This expansion is driven by several key factors. The increasing prevalence of cancer globally fuels the demand for efficient and comprehensive cancer care management systems. Advances in oncology treatment and research necessitate sophisticated information systems to handle complex patient data, treatment protocols, and clinical trials. Furthermore, the growing emphasis on value-based care and the need for improved patient outcomes are pushing healthcare providers to adopt OIS solutions for better data analysis, resource allocation, and clinical decision-making. The market is segmented into software and services, with software solutions commanding a significant share due to their ability to automate workflows, improve data accuracy, and enhance interoperability between various healthcare systems. Leading companies like Epic Systems Corp., McKesson Corp., and Elekta AB are investing heavily in research and development to enhance their offerings and consolidate their market positions. The competitive landscape is characterized by both established players and emerging innovative firms, leading to continuous advancements and enhanced functionality within the OIS sector. The regional distribution of the OIS market reflects the global cancer burden and healthcare infrastructure. North America, particularly the US, currently holds the largest market share, driven by high healthcare expenditure and technological advancements. However, regions like Asia-Pacific (APAC), specifically China and India, are witnessing rapid growth due to rising cancer incidence and increasing investments in healthcare IT infrastructure. Europe, with countries like Germany and the UK, also represents a significant market segment. While South America and the Middle East & Africa exhibit comparatively lower market penetration, the potential for growth remains considerable, given the increasing awareness about cancer and improving healthcare accessibility. The continued adoption of electronic health records (EHRs), the integration of artificial intelligence (AI) in oncology care, and the increasing focus on precision oncology are expected to further fuel the expansion of the OIS market in the coming years. However, challenges such as high implementation costs, data security concerns, and the need for ongoing system maintenance may act as potential restraints to market growth.

BackgroundClustering of gene expression data is widely used to identify novel subtypes of cancer. Plenty of clustering approaches have been proposed, but there is a lack of knowledge regarding their relative merits and how data characteristics influence the performance. We evaluate how cluster analysis choices affect the performance by studying four publicly available human cancer data sets: breast, brain, kidney and stomach cancer. In particular, we focus on how the sample size, distribution of subtypes and sample heterogeneity affect the performance.ResultsIn general, increasing the sample size had limited effect on the clustering performance, e.g. for the breast cancer data similar performance was obtained for n = 40 as for n = 330. The relative distribution of the subtypes had a noticeable effect on the ability to identify the disease subtypes and data with disproportionate cluster sizes turned out to be difficult to cluster. Both the choice of clustering method and selection method affected the ability to identify the subtypes, but the relative performance varied between data sets, making it difficult to rank the approaches. For some data sets, the performance was substantially higher when the clustering was based on data from only one sex compared to data from a mixed population. This suggests that homogeneous data are easier to cluster than heterogeneous data and that clustering males and females individually may be beneficial and increase the chance to detect novel subtypes. It was also observed that the performance often differed substantially between females and males.ConclusionsThe number of samples seems to have a limited effect on the performance while the heterogeneity, at least with respect to sex, is important for the performance. Hence, by analyzing the genders separately, the possible loss caused by having fewer samples could be outweighed by the benefit of a more homogeneous data.

BackgroundReduced overall survival has been observed in patients with left-sided versus right-sided breast cancer due to cardiac toxicity after radiotherapy. However, the effect of laterality and primary tumor site on breast cancer-specific mortality (BCSM) remains unclear.Patients and MethodsWe analyzed data from 305,443 women ages 20- to 79-years-old diagnosed with breast cancer between 1990 and 2009. The data were obtained from the population-based Surveillance, Epidemiology, and End Results (SEER) program of the U.S. National Cancer Institute. The survival outcomes with regard to laterality and primary tumor site were compared using univariate and multivariate (Cox proportional hazards regression model) methods.ResultsIn the multivariate analysis, BCSM was affected by the primary tumor site (P

This database of cancer-related citations for publications authored by CDC’s Division of Cancer Prevention and Control (DCPC) staff, fosters collaboration among scientists throughout the world. Allows for searching for links to scientific articles authored or co-authored by researchers from DCPC since 2000.

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Radiation Oncology Market Size 2024-2028

The radiation oncology market size is forecast to increase by USD 1.94 billion at a CAGR of4.34% between 2023 and 2028.

In the market, the primary drivers include the increasing incidence of cancer and the rise in healthcare expenditure. As cancer continues to be a significant health concern, the demand for advanced radiation therapy techniques, such as seeds and stereotactic therapy, is increasing. These treatments offer therapeutic benefits by targeting abnormal cells with precision, reducing the impact on healthy cells. Technological developments, including advanced treatment planning software, tumor tracking systems, artificial intelligence, and machine learning, enable more effective and personalized treatment plans. However, challenges persist, including the lack of access to radiotherapy in certain regions and the high cost of these advanced treatments. Despite these challenges, the market is expected to grow, driven by the potential for improved patient outcomes and the ongoing technological advancements In the field.

What will be the Size of the Radiation Oncology Market During the Forecast Period?

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The market is a significant segment of the healthcare industry, focusing on the delivery of radiation therapy to treat various types of cancer. This form of oncology treatment, also known as radiotherapy, utilizes high-energy radiation to destroy tumor cells. Radiation oncology plays a crucial role in cancer treatment, with breast cancer, metastatic melanoma, and neuroendocrine cancers being some of the common indications. The increasing prevalence of cancer and the growing demand for advanced therapeutic benefits have driven the market's growth. Regulatory scrutiny remains a critical factor In the market.



Stringent regulations ensure the safety and efficacy of radiotherapy devices and treatment planning software. These regulations also apply to advanced technologies like proton therapy, which offers improved therapeutic benefits for certain types of cancer. Imaging data plays a pivotal role in radiation oncology. Accurate and timely access to imaging data is essential for effective treatment planning and delivery. Cancer treatment centers and oncology research institutes are investing in advanced imaging technologies to enhance their capabilities. Technological developments in radiation oncology are continually evolving. Companies are focusing on improving the precision, efficiency, and patient experience of radiotherapy. Radiotherapy devices, such as those manufactured by Elekta and Gamma Knife, are being enhanced with innovative features.

How is this Radiation Oncology Industry segmented and which is the largest segment?

The radiation oncology industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Type

  EBRT
  Brachytherapy


Application

  Breast cancer
  Lung cancer
  Penile cancer
  Prostate cancer
  Others


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  Asia

    China


  Rest of World (ROW)

By Type Insights

The EBRT segment is estimated to witness significant growth during the forecast period.

Radiation oncology, a specialized medical field focusing on the use of radiation to treat various types of cancer, encompasses external beam radiation therapy (EBRT). EBRT utilizes high-energy beams, typically generated by a Linear Accelerator (LINAC, the most common technology), to target and destroy cancer cells. These beams can be delivered as X-rays, electrons, or other particles, such as protons. EBRT plays a crucial role in treating numerous cancer types, including breast cancer, colorectal cancer (CRC), cervical cancer, esophageal cancer, head and neck cancer, lung cancer, prostate cancer, and brain tumors. Advanced radiotherapy systems, such as CyberKnife, Gamma Knife, and TomoTherapy, are also part of the EBRT market.

Furthermore, proton therapy, which uses cyclotrons and synchrotrons, is another subset of EBRT. Among these technologies, LINAC holds the largest market share In the market. By providing precise and effective cancer treatment, these advanced technologies contribute significantly to cancer treatment centers across the US and North America, ensuring improved patient outcomes and quality of life.

Get a glance at the Radiation Oncology Industry report of share of various segments Request Free Sample

The EBRT segment was valued at USD 6.22 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

Europe is estimated to contribute 39% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends

Cancer is the quintessential complex disease. As technologies evolve faster each day, we are able to quantify the different layers of biological elements that contribute to the emergence and development of malignancies. In this multi-omics context, the use of integrative approaches is mandatory in order to gain further insights on oncological phenomena, and to move forward toward the precision medicine paradigm. In this review, we will focus on computational oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. We will discuss the current roles of computation in oncology in the context of multi-omic technologies, which include: data acquisition and processing; data management in the clinical and research settings; classification, diagnosis, and prognosis; and the development of models in the research setting, including their use for therapeutic target identification. We will discuss the machine learning and network approaches as two of the most promising emerging paradigms, in computational oncology. These approaches provide a foundation on how to integrate different layers of biological description into coherent frameworks that allow advances both in the basic and clinical settings.

The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who are receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites.

This collection contains de-identified radiology and histopathology imaging procured from subjects in NCI’s Cancer Moonshot Biobank - Prostate Cancer (CMB-PCA) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases. A summary of Cancer Moonshot Biobank imaging efforts can be found on the Cancer Moonshot Biobank Imaging page.

Oncology Informatics Market size was valued at USD 12.1 Billion in 2023 and is projected to reach USD 33.5 Billion by 2030, growing at a CAGR of 12% during the forecast period 2024-2030.

The Global Oncology Informatics Market is mainly driven by the increasing cost of cancer treatment, a growing number of cancer patients, and the rising adoption of oncology-specific EHR’s. The Global Oncology Informatics Market report provides a holistic evaluation of the market. The report offers a comprehensive analysis of key segments, trends, drivers, restraints, competitive landscape, and factors that are playing a substantial role in the market.

Increasing Cancer Rates: As cancer is becoming more commonplace worldwide, there is a need for improved instruments for research, diagnosis, and treatment, which is why oncology informatics solutions are becoming more popular.

Technological Advancements: Cloud computing, big data analytics, and artificial intelligence (AI) are transforming healthcare data analysis and administration in oncology.

Emphasis on Precision Medicine: Utilizing patient-specific genetic information and medical records, oncology informatics aids in the customization of cancer treatment regimens.

Enhanced Clinical Workflow Efficiency: By streamlining healthcare workers’ workflows, oncology informatics frees them up to spend more time caring for patients.

Better Patient Care: Better communication technologies and real-time patient data access provide better patient care coordination and results.

Global Oncology Adjuvants Market was valued at $2.57 Billion in 2023, and is projected to $USD 5.58 Billion by 2032, at a CAGR of 9% from 2023 to 2032.

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. REMBRANDT is a data repository containing diverse types of molecular research and clinical trials data related to brain cancers, including gliomas, along with a wide variety of web-based analysis tools that readily facilitate the understanding of critical correlations among the different data types. REMBRANDT aims to be the access portal for a national molecular, genetic, and clinical database of several thousand primary brain tumors that is fully open and accessible to all investigators (including intramural and extramural researchers), as well as the public at-large. The main focus is to molecularly characterize a large number of adult and pediatric primary brain tumors and to correlate those data with extensive retrospective and prospective clinical data. Specific data types hosted here are gene expression profiles, real time PCR assays, CGH and SNP array information, sequencing data, tissue array results and images, proteomic profiles, and patients'''' response to various treatments. Clinical trials'''' information and protocols are also accessible. The data can be downloaded as raw files containing all the information gathered through the primary experiments or can be mined using the informatics support provided. This comprehensive brain tumor data portal will allow for easy ad hoc querying across multiple domains, thus allowing physician-scientists to make the right decisions during patient treatments.

QResearch linked National Cancer Registration and Analysis Service (NCRAS) cancer registration data contain a record for each notified, registrable tumour, diagnosed or treated in England.