Common Scientific Outline (CSO)

Awards on the International Cancer Research Partnership (ICRP) database are coded using a common language — the Common Scientific Outline or 'CSO', a classification system organized into six broad areas of scientific interest in cancer research. The CSO is complemented by a standard cancer type coding scheme. Together, these tools lay a framework to improve coordination among research organizations, making it possible to compare and contrast the research portfolios of public, non-profit, and governmental research agencies. In the section below, you can browse the CSO and see examples of research in each area. Links to the CSO in other languages, and training guides are provided in the download area. The current version (v2) of the CSO was adopted by the International Cancer Research Partnership in April 2015 and all awards in the database are coded to this version. To register as a CSO user, or to receive training in its use, please contact us.

Biology

Research included in this category looks at the biology of how cancer starts and progresses as well as normal biology relevant to these processes

1.1 Normal Functioning Example Example

Examples of science that would fit:

  • Developmental biology (from conception to adulthood) and the biology of aging
  • Normal functioning of genes, including their identification and expression, and the normal function of gene products, such as hormones and growth factors
  • Normal formation of the extracellular matrix
  • Normal cell-to-cell interactions
  • Normal functioning of apoptotic pathways
  • Characterization of pluripotent progenitor cells (e.g., normal stem cells)

1.2 Cancer Initiation: Alterations in Chromosomes Example Example

Examples of science that would fit:

  • Abnormal chromosome number
  • Aberration in chromosomes and genes (e.g., in chronic myelogenous leukemia)
  • Damage to chromosomes and mutation in genes
  • Failures in DNA repair
  • Aberrant gene expression
  • Epigenetics
  • Genes and proteins involved in aberrant cell cycles

1.3 Cancer Initiation: Oncogenes and Tumor Suppressor Genes Example Example

Examples of science that would fit:

  • Genes and signals involved in growth stimulation or repression, including oncogenes (Ras, etc.), and tumor suppressor genes (p53, etc.)
  • Effects of hormones and growth factors and their receptors such as estrogens, androgens, TGF-beta, GM-CSF, etc.
  • Research into the biology of stem cell tumour initiation

1.4 Cancer Progression and Metastasis Example Example

Examples of science that would fit:

  • Latency, promotion, and regression
  • Expansion of malignant cells
  • Interaction of malignant cells with the immune system or extracellular matrix
  • Cell mobility, including detachment, motility, and migration in the circulation
  • Invasion
  • Malignant cells in the circulation, including penetration of the vascular system and extravasation
  • Systemic and cellular effects of malignancy
  • Tumor angiogenesis and growth of metastases
  • Role of hormone or growth factor dependence/independence in cancer progression
  • Research into cancer stem cells supporting or maintaining cancer progression
  • Interaction of immune system and microbiome in cancer progression

1.5 Resources and Infrastructure Example Example

Examples of science that would fit:

  • Informatics and informatics networks
  • Specimen resources
  • Epidemiological resources pertaining to biology
  • Reagents, chemical standards
  • Development and characterization of new model systems for biology, distribution of models to scientific community or research into novel ways of applying model systems, including but not limited to computer-simulation systems, software development, in vitro/cell culture models, organ/tissue models or animal model systems.
  • Education and training of investigators at all levels (including clinicians and other health professionals), such as participation in training workshops, conferences, advanced research technique courses, and Master's course attendance. This does not include longer-term research-based training, such as Ph.D. or post-doctoral fellowships.

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Etiology

Research included in this category aims to identify the causes or origins of cancer - genetic, environmental, and lifestyle, and the interactions between these factors.

2.1 Exogenous Factors in the Origin and Cause of Cancer Example Example

Examples of science that would fit:

  • Research into the role of lifestyle factors such as smoking, chewing tobacco, alcohol consumption, parity, diet, sunbathing, and exercise in the origin and cause of cancer or increasing the risk of cancer
  • Research into the social determinants of cancer such as crime, housing dilapidation (poor housing), neighbourhood level socioeconomic status and services and their relationship to cancer incidence and mortality etc.
  • Studies on the effect(s) of nutrients or nutritional status on cancer incidence
  • Development, characterization, validation, and use of dietary/nutritional assessment instruments in epidemiological studies and to evaluate cancer risk
  • Environmental and occupational exposures such as radiation, second-hand smoke / e-cigarettes, radon, asbestos, organic vapors, pesticides, and other chemical or physical agents
  • Infectious agents associated with cancer etiology, including viruses (Human Papilloma Virus-HPV, etc.) and bacteria (helicobacter pylori, etc.)
  • Viral oncogenes and viral regulatory genes associated with cancer causation
  • Contextual factors contributing to cancer incidence (e.g., race/ethnicity, socioeconomic status, neighborhood factors, community factors, built environment).

2.2 Endogenous Factors in the Origin and Cause of Cancer Example Example

Examples of science that would fit:

  • Free radicals such as superoxide and hydroxide radicals
  • Identification /confirmation of genes suspected of being mechanistically involved in familial cancer syndromes; for example, BRCA1, Ataxia Telangiectasia, and APC
  • Identification/confirmation of genes suspected or known to be involved in "sporadic" cancer events; for example, polymorphisms and/or mutations that may affect carcinogen metabolism (e.g., CYP, NAT, glutathione transferase, etc.)
  • Investigating a role for stem cells in the etiology of tumours

2.3 Interactions of Genes and/or Genetic Polymorphisms with Exogenous and/or Endogenous Factors Example Example

Examples of science that would fit:

  • Gene-environment interactions, including research into the role of the microbiome
  • Interactions of genes with lifestyle factors, environmental, and/or occupational exposures such as variations in carcinogen metabolism associated with genetic polymorphisms
  • Interactions of genes and endogenous factors such as DNA repair deficiencies and endogenous DNA damaging agents such as oxygen radicals or exogenous radiation exposure

2.4 Resources and Infrastructure Related to Etiology Example Example

Examples of science that would fit:

  • Informatics and informatics networks; for example, patient databanks
  • Specimen resources (serum, tissue, etc.)
  • Reagents and chemical standards
  • Epidemiological resources pertaining to etiology
  • Statistical methodology or biostatistical methods
  • Centers, consortia, and/or networks
  • Development, characterization and validation of new model systems for etiology, distribution of models to the scientific community or research into novel ways of applying model systems, including but not limited to computer-simulation systems, software development, in vitro/cell culture models, organ/tissue models or animal model systems. Note: this should only be used where the focus of the award is creating a model. If it is only a tool or a methodology, code to the research instead.
  • Education and training of investigators at all levels (including clinicians and other health professionals), such as participation in training workshops, conferences, advanced research technique courses, and Master's course attendance. This does not include longer term research based training, such as Ph.D. or post-doctoral fellowships.

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Prevention

Research included in this category looks at identifying individual and population-based primary prevention interventions, which reduce cancer risk by reducing exposure to cancer risks and increasing protective factors.

3.1 Interventions to Prevent Cancer: Personal Behaviors (Non-Dietary) that Affect Cancer Risk Example Example

Examples of science that would fit:

  • Research on determinants of personal behaviors, such as physical activity, sun exposure, alcohol and tobacco use, known to affect cancer risk and interventions (including educational and behavioral interventions, such as e-cigarettes, directed at individuals as well as population-based interventions including social marketing campaigns, environmental supports, and regulatory, policy and legislative changes) to change determinants or to target health inequalities.
  • Directed education to specified populations of patients, health care providers, and at-risk groups about cancer risk and prevention and relevant interventions with the intent of promoting increased awareness and behavioural change. This includes communication of lifestyle models that reduce cancer risk, such as communicating smoking and tobacco cessation interventions, genetic counselling, or targeting/addressing health inequalities.

3.2 Dietary Interventions to Reduce Cancer Risk and Nutritional Science in Cancer Prevention Example Example

Examples of science that would fit:

  • Quantification of nutrients, micronutrients, and purified nutritional compounds in cancer prevention studies
  • Development, characterization, validation, and use of dietary/nutritional assessment instruments to evaluate cancer prevention interventions
  • Research on determinants of dietary behavior and interventions to change diet (including educational and behavioral interventions directed at individuals as well as population-based interventions including social marketing campaigns, environmental supports, and regulatory and legislative changes)
  • Education of patients, health care providers, at-risk populations, and the general population about cancer risk and diet
  • Communicating cancer risk of diet to underserved populations, at-risk populations, and the general public
  • Communication of nutritional interventions that reduce cancer risk
  • Nutritional manipulation of the microbiome for cancer prevention

3.3 Chemoprevention and other medical interventions Example Example

Examples of science that would fit:

  • Chemopreventive agents and their discovery, mechanism of action, development, testing in model systems, and clinical testing
  • Other (non-vaccine) preventive measures such as prophylactic surgery (e.g., mastectomy, oophorectomy, prostatectomy etc.), use of antibiotics, immune modulators/stimulators or other biological agents.
  • Manipulation of the microbiome for cancer prevention (e.g., fecal transplant)

3.4 Vaccines Example Example

Examples of science that would fit:

  • Vaccines for prevention, their discovery, mechanism of action, development, testing in model systems, and clinical testing (e.g., HPV vaccines)

3.5 Complementary and Alternative Prevention Approaches Example Example

Examples of science that would fit:

  • Discovery, development, and testing of complementary/alternative medicine (CAM) approaches or other primary prevention interventions that are not widely used in conventional medicine or are being applied in different ways as compared to conventional medical uses
  • Mind and body medicine (e.g., meditation, acupuncture, hypnotherapy), manipulative and body-based practices (e.g., spinal manipulation, massage therapy), and other practices (e.g., light therapy, traditional healing) used as a preventive measure.

3.6 Resources and Infrastructure Related to Prevention Example Example

Examples of science that would fit:

  • Informatics and informatics networks; for example, patient databanks
  • Specimen resources (serum, tissue, etc.)
  • Epidemiological resources pertaining to prevention
  • Clinical trials infrastructure
  • Statistical methodology or biostatistical methods
  • Centers, consortia, and/or networks
  • Development and characterization of new model systems for prevention, distribution of models to scientific community or research into novel ways of applying model systems, including but not limited to computer-simulation systems, software development, in vitro/cell culture models, organ/tissue models or animal model systems. Note: this should only be used where the focus of the award is creating a model. If it is only a tool or a methodology, code to the research instead.
  • Education and training of investigators at all levels (including clinicians and other health professionals), such as participation in training workshops, conferences, advanced research technique courses, and Master's course attendance. This does not include longer term research based training, such as Ph.D. or post-doctoral fellowships.

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Early Detection, Diagnosis, and Prognosis

Research included in this category focuses on identifying and testing cancer markers, imaging and other methods that are helpful in detecting and/or diagnosing cancer as well as predicting the outcome or chance of recurrence or to support treatment decision making in stratified/personalised medicine.

4.1 Technology Development and/or Marker Discovery Example Example

Examples of science that would fit:

  • Discovery or identification and characterization of markers (e.g., proteins, genes, epigenetic, microbiomic), and/or technologies (such as fluorescence, nanotechnology, etc.) that are potential candidates for use in cancer detection, staging, diagnosis, theranostic and/or prognosis
  • Use of proteomics, genomics, expression assays, or other technologies in the discovery or identification of markers
  • Defining molecular signatures of cancer cells, including cancer stem cells (e.g., for the purposes of diagnosis/prognosis/theranostic and to enable treatment decision planning in personalized/stratified/precision medicine)

4.2 Technology and/or Marker Evaluation With Respect to Fundamental Parameters of Method Example Example

Examples of science that would fit:

  • Development, refinement, and preliminary evaluation (e.g., animal trials, preclinical, and Phase I human trials) of identified markers or technologies such as genetic/protein biomarkers (prospective or retrospective) or imaging methods (optical probes, PET, MRI, etc.)
  • Preliminary evaluation with respect to laboratory sensitivity, laboratory specificity, reproducibility, and accuracy
  • Research into mechanisms assessing tumor response to therapy at a molecular or cellular level

4.3 Technology and/or Marker Testing in a Clinical Setting Example Example

Examples of science that would fit:

  • Evaluation of clinical sensitivity, clinical specificity, and predictive value (Phase II or III clinical trials), including theranostics and prediction of late/adverse events
  • Quality assurance and quality control
  • Inter- and intra-laboratory reproducibility
  • Testing of the method with respect to effects on morbidity and/or mortality
  • Study of screening methods, including compliance, acceptability to potential screenees, and receiver-operator characteristics. Includes education, communication (e.g., genetic counselling and advice on screening behavior based on cancer risk factors), behavioral and complementary/alternative approaches to improve compliance, acceptability or to reduce anxiety/discomfort, and evaluation of new methods to improve screening in healthcare settings.
  • Research into improvements in techniques to assess clinical response to therapy

4.4 Resources and Infrastructure Related to Detection, Diagnosis, or Prognosis Example Example

Examples of science that would fit:

  • Informatics and informatics networks; for example, patient databanks
  • Specimen resources (serum, tissue, images, etc.)
  • Clinical trials infrastructure
  • Epidemiological resources pertaining to risk assessment, detection, diagnosis, or prognosis
  • Statistical methodology or biostatistical methods
  • Centers, consortia, and/or networks
  • Development, characterization and validation of new model systems for detection, diagnosis or prognosis, distribution of models to the scientific community or research into novel ways of applying model systems, including but not limited to computer-simulation systems, software development, in vitro/cell culture models, organ/tissue models or animal model systems. Note: this should only be used where the focus of the award is creating a model. If it is only a tool or a methodology, code to the research instead.
  • Education and training of investigators at all levels (including clinicians and other health professionals), such as participation in training workshops, conferences, advanced research technique courses, and Master's course attendance. This does not include longer term research based training, such as Ph.D. or post-doctoral fellowships.

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Treatment

Research included in this category focuses on identifying and testing treatments administered locally (such as radiotherapy and surgery) and systemically (treatments like chemotherapy which are administered throughout the body) as well as non-traditional (complementary/alternative) treatments (such as supplements, herbs). Research into the prevention of recurrence and treatment of metastases are also included here.

5.1 Localized Therapies - Discovery and Development Example Example

Examples of science that would fit:

  • Discovery and development of treatments administered locally that target the organ and/or neighboring tissue directly, including but not limited to surgical interventions, cryotherapy, local/regional hyperthermia, high-intensity, focused ultrasound, radiotherapy, and brachytherapy
  • Therapies with a component administered systemically but that act locally (e.g., photodynamic therapy, radioimmunotherapy, radiosensitizers and theranostics)
  • Development of methods of localized drug delivery of systemic therapies e.g., Pressurized Intraperitoneal Aerosol Chemotherapy (PIPAC), direct intratumoral polymers / gels / nanoparticles / microsomes etc.
  • Research into the development of localized therapies to prevent recurrence
  • Identifying mechanisms of action of existing localized therapies and targets, including cancer stem cells.

5.2 Localized Therapies - Clinical Applications Example Example

Examples of science that would fit:

  • Clinical testing and application of treatments administered locally that target the organ and/or neighboring tissue directly, including but not limited to surgical interventions, cryotherapy, local/regional hyperthermia, radiotherapy, and brachytherapy.
  • Clinical testing and application of therapies with a component administered systemically but that act locally (e.g., photodynamic therapy, radiosensitizers and theranostics, Pressurized Intraperitoneal Aerosol Chemotherapy (PIPAC), direct intratumoral polymers / gels / nanoparticles / microsomes etc.
  • Phase I, II, or III clinical trials of promising therapies that are administered locally
  • Side effects, toxicity, and pharmacodynamics
  • Clinical testing of localized therapies to prevent recurrence and prevent and treat metastases

5.3 Systemic Therapies - Discovery and Development Example Example

Examples of science that would fit:

  • Discovery and development of treatments administered systemically such as cytotoxic or hormonal agents, novel systemic therapies such as immunologically directed therapies (treatment vaccines, antibodies , antibiotics, theranostics or other biologics), gene therapy, angiogenesis inhibitors, apoptosis inhibitors, whole body hyperthermia, bone marrow/stem cell transplantation, differentiating agents, adjuvant and neo-adjuvant treatments, systemically-delivered nanoparticles/microsomes, cell-based therapies, manipulation of the microbiome etc.
  • Identifying mechanisms of action of existing cancer drugs and novel drug targets, including cancer stem cells for the purposes of treatment/identifying drug targets
  • Drug discovery and development, including drug metabolism, pharmacokinetics, pharmacodynamics, combinatorial chemical synthesis, drug screening, development of high-throughput assays, and testing in model systems, including that which may aid treatment planning in stratified/personalised medicine
  • Investigating the molecular mechanisms of drug resistance (including the role of cancer stem cells) and pre-clinical evaluation of therapies to circumvent resistance
  • Development of methods of drug delivery
  • Research into the development of systemic therapies to prevent recurrence

5.4 Systemic Therapies - Clinical Applications Example Example

Examples of science that would fit:

  • Clinical testing and application of treatments administered systemically such as cytotoxic or hormonal agents, novel systemic therapies such as immunologically directed therapies (treatment vaccines, antibodies, antibiotics, theranostics or other biologics), gene therapy, angiogenesis inhibitors, apoptosis inhibitors, whole body hyperthermia, bone marrow/stem cell transplantation, differentiating agents, adjuvant and neo-adjuvant treatments, systemically-delivered nanoparticles/microsomes, cell-based therapies, manipulation of the microbiome etc.
  • Phase I, II, or III clinical trials of promising therapies administered systemically
  • Side effects, toxicity, and pharmacodynamics
  • Clinical testing of systemic therapies to prevent recurrence and prevent and treat metastases

5.5 Combinations of Localized and Systemic Therapies Example Example

Examples of science that would fit:

  • Development and testing of combined local and systemic approaches to treatment (e.g., radiotherapy and chemotherapy, or surgery and chemotherapy)
  • Clinical application of combined approaches to treatment such as systemic cytotoxic therapy and radiation therapy
  • Development and clinical application of combined localized and systemic therapies to prevent recurrence and prevent and treat metastases

5.6 Complementary and Alternative Treatment Approaches Example Example

Examples of science that would fit:

  • Discovery, development, and clinical application of complementary/alternative medicine (CAM) treatment approaches such as diet, herbs, supplements, natural substances, or other interventions that are not widely used in conventional medicine or are being applied in different ways as compared to conventional medical uses
  • Complementary/alternative or non-pharmaceutical approaches to prevent recurrence and prevent and treat metastases

5.7 Resources and Infrastructure Related to Treatment and the Prevention of Recurrence Example Example

Examples of science that would fit:

  • Informatics and informatics networks; for example, clinical trials networks and databanks
  • Mathematical and computer simulations
  • Specimen resources (serum, tissue, etc.)
  • Clinical trial groups
  • Clinical treatment trials infrastructure
  • Epidemiological resources pertaining to treatment
  • Statistical methodology or biostatistical methods
  • Drugs and reagents for distribution and drug screening infrastructures
  • Centers, consortia, and/or networks
  • Development and characterization of new model systems for treatment, distribution of models to scientific community or research into novel ways of applying model systems, including but not limited to computer-simulation systems, software development, in vitro/cell culture models, organ/tissue models or animal model systems. Note: this should only be used where the focus of the award is creating a model. If it is only a tool or a methodology, code to the research instead.
  • Reviews/meta-analyses of clinical effectiveness of therapeutics/treatments
  • Education and training of investigators at all levels (including clinicians and other health professionals), such as participation in training workshops, conferences, advanced research technique courses, and Master's course attendance. This does not include longer term research based training, such as Ph.D. or post-doctoral fellowships.

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Cancer Control, Survivorship, and Outcomes Research

Research included in this category includes a broad range of areas: patient care and pain management; tracking cancer cases in the population; beliefs and attitudes that affect behavior regarding cancer control; ethics; education and communication approaches for patients, family/caregivers, and health care professionals; supportive and end-of-life care; and health care delivery in terms of quality and cost effectiveness.

6.1 Patient Care and Survivorship Issues Example Example

Examples of science that would fit:

  • Research into patient centred outcomes
  • Quality of life
  • Pain management
  • Psychological impacts of cancer survivorship
  • Rehabilitation, including reconstruction and replacement
  • Economic sequelae, including research on employment, return to work, and vocational/educational impacts on survivors and their families/caregivers
  • Reproductive issues
  • Long-term issues (morbidity, health status, social and psychological pathways)
  • Symptom management, including nausea, vomiting, lymphedema, neuropathies, etc.
  • Prevention and management of long-term treatment-related toxicities and sequelae, including symptom management (e.g., physical activity or other interventions), prevention of mucosities, prevention of cardiotoxicities, opportunistic infections, cachexia etc.
  • Psychological, educational or complementary/alternative (e.g., hypnotherapy, relaxation, transcendental meditation, imagery, spiritual healing, massage, biofeedback, herbs, spinal manipulation, yoga, acupuncture) interventions/approaches to promote behaviors that lessen treatment-related morbidity and promote psychological adjustment to the diagnosis of cancer and to treatment effects
  • Burdens of cancer on family members/caregivers and interventions to assist family members/caregivers
  • Educational interventions to promote self-care and symptom management
  • Research into peer support, self-help, and other support groups
  • Behavioral factors in treatment compliance

6.2 Surveillance Example Example

Examples of science that would fit:

  • Epidemiology and end results reporting (e.g., SEER)
  • Registries that track incidence, morbidity, co-morbidities/symptoms, long-term effects and/or mortality related to cancer
  • Surveillance, measurement, evaluation or tracking of established cancer risk factors in populations such as diet, body weight, physical activity, sun exposure, and tobacco use, including method development
  • Analysis of variations in established cancer risk factor exposure in populations by demographic, geographic, economic, or other factors
  • Trends in use of interventional strategies in populations (e.g., geographic variation)

6.3 Population-based Behavioral Factors Example Example

Examples of science that would fit:

  • Research into populations’ attitudes and belief systems (including cultural beliefs) and their influence on behaviors related to cancer control, outcomes and treatment. For example, how populations’ beliefs can affect compliance/interaction with all aspects of the health care/service provision
  • Research into the psychological effects of genetic counselling
  • Research into behavioral barriers to improving cancer care/survivorship clinical trial enrolment

6.4 Health Services, Economic and Health Policy Analyses Example Example

Examples of science that would fit:

  • Development and testing of health service delivery methods
  • Interventions to increase the quality of health care delivery
  • Impact of organizational, social, and cultural factors on access to care and quality of care, including studies on variations or inequalities in access among racial, ethnic, geographical or socio-economic groups
  • Studies of providers such as geographical or care-setting variations in outcomes
  • Effect of reimbursement and/or insurance on cancer control, outcomes, and survivorship support
  • Health services research, including health policy and practice and development of guidelines/best practice for healthcare delivery across the diagnostic/ preventive/ treatment spectrum
  • Analysis of health service provision, including the interaction of primary and secondary care
  • Analyses of the cost effectiveness of methods used in cancer prevention, detection, diagnosis, prognosis, treatment, and survivor care/support
  • Ethical, legal or social implications of research/health service delivery (e.g. genetic counselling)
  • Research into systemic or operational barriers to trial enrolment

6.5 Education and Communication Research Example Example

Examples of science that would fit:

  • Development of generic health provider-patient communication tools and methods (e.g., telemedicine/health)
  • Tailoring educational approaches or communication to different populations (e.g., social, racial, geographical, or linguistic groups)
  • Research into new educational and communication methods and approaches, including special approaches and considerations for underserved and at-risk populations
  • Research on new methods and strategies to disseminate cancer information/innovation to healthcare providers (e.g., web-based information, telemedicine, smartphone apps, etc.) and the effectiveness of these approaches
  • Research on new communication processes and/or media and information technologies within the health care system and the effectiveness of these approaches
  • Media studies focused on the nature and ways in which information on cancer and cancer research findings are communicated to the general public
  • Education, information, and assessment systems for the general public, primary care professionals, or policy makers
  • Research into barriers to successful health communication

6.6 End-of-Life Care Example Example

Examples of science that would fit:

  • Hospice/end-of-life patient care focused on managing pain and other symptoms (e.g., respiratory distress, delirium, cachexia) and the provision of psychological, social, spiritual and practical support through either conventional or complementary/alternative interventions/approaches throughout the last phase of life and into bereavement
  • Quality of life and quality of death for terminally-ill patients
  • Provision of psychological, social, spiritual and practical support to families/caregivers through either conventional or complementary/alternative interventions/approaches
  • Research into the delivery of hospice care

6.7 Research on Ethics and Confidentiality Example Example

Examples of science that would fit:

  • Informed consent modeling/framing and development
  • Quality of Institutional Review Boards (IRBs)
  • Protecting patient confidentiality and privacy
  • Research on publication bias within the cancer research field

6.9 Resources and Infrastructure Related to Cancer Control, Survivorship, and Outcomes Research Example Example

Examples of science that would fit:

  • Informatics and informatics networks
  • Clinical trial groups related to cancer control, survivorship, and outcomes research
  • Epidemiological resources pertaining to cancer control, survivorship, and outcomes research
  • Statistical methodology or biostatistical methods pertaining to cancer control, survivorship and outcomes research
  • Surveillance infrastructures
  • Centers, consortia, and/or networks pertaining to cancer control, survivorship and outcomes research
  • Development and characterization of new model systems for cancer control, outcomes or survivorship, distribution of models to scientific community or research into novel ways of applying model systems, including but not limited to computer-simulation systems, software development, in vitro/cell culture models, organ/tissue models or animal model systems. Note: this should only be used where the focus of the award is creating a model. If it is only a tool or a methodology, code to the research instead.
  • Psychosocial, economic, political and health services research frameworks and models
  • Education and training of investigators at all levels (including clinicians and other health professionals), such as participation in training workshops, conferences, advanced research technique courses, and Master's course attendance. This does not include longer-term research-based training, such as Ph.D. or post-doctoral fellowships.

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CSO Last Revised: April 2015