Researchers are invited to apply for R01 and R21 grants in five thematic areas. Letters of Intent are due December 16, 2013 and applications are due January 15, 2014. The NCI anticipates publication of the new FOAs in late September/early October 2013.
Group A: Cancer Prevention and Risk
PQA - 1: How do decision making processes influence habitual behaviors, and how can that knowledge be used to design strategies that lead to adoption and maintenance of behaviors that reduce cancer risk?
Background: A wealth of epidemiological research shows that certain modifiable and habitual behaviors are linked to increased cancer risk; these include tobacco use, UV exposure and obesity-related behaviors such as overeating and physical inactivity. Despite awareness of the link between these behaviors to the risk of cancer and other diseases, many individuals find it difficult to change those behaviors. Research on basic decision-making processes, emotion, and motivation, could shed light on why people fail to alter behavioral patterns and could inform the development of interventions to increase healthy behaviors and ultimately improve cancer outcomes.
Feasibility: Opportunities exist to leverage methodological perspectives and tools from sciences (e.g., marketing and consumer science, industrial and organizational psychology, neuroscience) far afield of traditional cancer research to understand and change behaviors known to increase cancer risk.
Implications of success: Reduced cancer morbidity and mortality as a result of modified health behaviors associated with disease risk.
PQA - 2: How does the level, type, or duration of physical activity influence cancer risk and prognosis?
Background: Several studies have shown that physical activity has important but poorly understood features that lower cancer risk and positively affect the progression of tumor development. These effects are not just due to weight loss or caloric restriction. This Provocative Question seeks studies to determine what features or types of physical activity are most important in achieving these benefits, and what is the mechanism underlying these effects.
Feasibility: Researchers may be able to expand or utilize existing studies or possibly initiate new studies to learn what components of physical activity affect cancer incidence or progression. Among the important features that could be studied are: What types of physical activity, ranging from active life style to aerobic or anaerobic workout programs, lead to these benefits? Is the length of activity or the intensity key to the advantages? What molecular changes induced by physical activity might be linked to the beneficial effects?
Implications of success: Better understanding of how physical activity affects cancer will lead to stronger and better recommendations about healthy life style. Eventual understanding of the molecular causes for such benefits could lead to better understanding of what physiological events could serve as models to future prevention research.
PQA - 3: What biological mechanisms influence susceptibility to cancer risk factors at various stages of life?
Background: Cells and tissues in various developmental stages will respond differently to risk exposures. A simple well-known example of differential response is seen for cells in early development, which may be more susceptible to exposures that rely on DNA synthesis than when cells reach adult stages where division is less common. Similarly, exposure risks may be more important when cells are in other stages or under other types of pressures. This Provocative Question seeks experimental approaches that can be used to distinguish when risks are most dangerous and then asks what molecular mechanisms underlie these differences.
Feasibility: Since the measurement of changes induced by risk factor exposure is key to success for this question, it will be essential to identify appropriate systems for study. Starting new longitudinal studies in humans is beyond the scope of this question; therefore, applicants are encouraged to identify other systems where exposure effects can be linked to various outcomes and studied in more detail. Experiments in mice will provide one potential system where both the effect and outcome of exposure can be measured and studied. In addition, some existing human exposure samples may be available for such studies. The goal of these experiments is to move beyond simple observational studies and determine what molecular mechanisms account for the differential responses to risk exposure.
Implications of success: Learning what cellular processes promote and inhibit the effects of exposure will help us understand important variations in the early stages of tumor development. These differences will provide needed insight into how one might identify targets for prevention and early detection. Such information will also help the community prepare better guidance for the management of risk.
PQA - 4: For tumors that arise from a pre-malignant field, what properties of cells in this field can be used to design strategies to inhibit the development of future tumors?
Background: Several lines of experimentation have shown cells that surround solid tumors often carry mutations or epigenetic changes characteristic of the tumor itself. These cells appear normal or at least more like normal cells than the tumor, but their genetic or epigenetic changes suggest that they may be derived from the same precursor cell that led to the tumor. This Provocative Question expands on these observations and asks for experimental approaches that might use the changes seen in surrounding cells as potential targets to prevent the appearance of future tumors from these fields.
Feasibility: Investigators will need to identify a useful tumor development model to study these types of changes. These could be in the mouse or there may be specific tumor and nearby non-tumor samples available for some human tissues. Comparisons using omic style studies would be the most likely source for the identification of potential similarities in tumors and surrounding cells but not in more distant normal cells. These then could be used to build and test hypotheses about new targets for treatment or prevention of future tumor development.
Implications of success: The results from these studies will provide a useful tumor development model for the identification of early stage lesions. Comparison of responses with drugs targeting early stage lesions versus late stage lesions will help us understand the importance of choosing among various targets based on their stage of appearance. In addition, such studies might suggest diagnostic steps that could identify early lesions and thus might help prioritize target selection. Similarly it may be possible to design trials to block the development of future tumors based on the identification of the earliest lesions. Finally, the classification of lesions as either early or late promises to help us understand the development pattern of certain tumor mutations.
Group B: Mechanisms of Tumor Development or Recurrence
PQB - 1: Why do second, independent cancers occur at higher rates in patients who have survived a primary cancer than in a cancer-naïve population?
Background: Second cancers are a major problem for cancer survivors. Grouped as a single outcome in the Surveillance Epidemiology and End Results (SEER) database, second cancers rank fourth in overall cancer incidence and are often associated with poor outcomes. However, researchers have not taken full advantage of this population to study risk factors and mechanisms. The influence of prior therapeutic interventions (including chemo- and radio-therapies) and somatic mutations in this population has been studied to some degree. However, the extent to which underlying genetic predispositions, environmental factors, and life-style behaviors influence risk remain relatively underexplored. It is likely that at least some of the contributing risk factors and mechanisms would be relevant to all cancer patients, not only those with second independent cancers.
Feasibility: Given the high risk of these developing in cancer patients and their involvement with medical oncology personnel, it should be substantially easier to monitor cancer survivors for the development of a second cancer than to observe healthy individuals for the development of a first cancer. Cancer survivors are often followed prospectively for treatment response and complications, as well as disease progression. Technologies that identify somatic alterations can be integrated with genome-wide annotation of germ-line DNA to investigate the relationship between genetic susceptibility in high-risk individuals and second cancers. With the advent of new, more efficient technologies, it is feasible to broaden these efforts to large-scale clinical trial studies. Efforts to capture clinical, epidemiological, and therapeutic data could also be centered on the development of large-scale cohorts of cancer survivors at risk for second cancers. Because of their heightened risk of cancer, this population of patients may be more motivated, and therefore well suited, for prospective prevention studies, such as chemoprevention or behavioral modifications.
Implications of success: Studying patients who have had primary cancers for the development of second cancers could help uncover pathogenic mechanisms of both cancers, including shared etiologic pathways and therapy-related risks. These insights are likely to inform new strategies for preventive interventions.
PQB - 2: What molecular and cellular events in the tumor microenvironment (for example, the local immune response) determine if a tumor at the earliest stages of malignant transformation is eliminated, stimulated for further development, or made indolent?
Background: It is now thought that the tumor microenvironment plays conflicting roles during the earliest stages of cancer development. For example, the immune response may have both the capacity to eliminate transformed cells or promote their tumorigenic potential. Recent reports have suggested that within hours after an oncogenic event, transformed cells secrete danger signals that attract innate immune cells. The role of early immune responses is not well understood. Importantly, the nature of the immune response could have profound consequences in determining whether tumors are eliminated or allowed to progress. It is likely that other interactions between the developing tumor and its microenvironment may also have both positive and negative roles in how the tumor develops. This Provocative Question seeks to determine what critical events in the microenvironment at this early stage determine whether a pre-emergent tumor is eliminated or allowed to progress.
Feasibility: An important prerequisite for studies in response to this question will be the selection of appropriate systems to study the tumor microenvironment during the very first stages of transformation. Genetically engineered mouse models might provide a good system to begin such studies or there may be a well understood human tumor development system that could be used. Characterization of well-known features of the tumor microenvironment or tumor immune response mechanisms at these earliest stages may provide a useful starting point for studies. These stages may also lend themselves to high-throughput profiling or other omic-style studies to help characterize these events.
Implications of success: Understanding the earliest responses within the microenvironment to the emerging tumor cell promises to be one of the best points to influence the course of malignancy development. The ability either to manipulate these responses towards elimination or to block any enhancement of tumor development could be used to identify new targets for therapy or for prevention.
PQB - 3: What mechanisms initiate or sustain cancer cachexia, and can we target them to extend lifespan and quality of life for cancer patients?
Background: Cachexia, or wasting syndrome, is a common, devastating condition seen in many patients with late stage cancer. When present, cachexia will almost certainly be a contributor to death. Although there have been several previous periods of intense research focus on cachexia, we still know little about what signals its initiation or maintenance. This Provocative Question calls for new studies on the biology of cachexia, the signals that are important for its regulation, and the reasons why it resists reversal.
Feasibility: Modern methods of biological characterization promise to generate new information about the process and control of cachexia. Omic studies of affected tissues and of tumors themselves may provide new clues to its origins and the inability to reverse its course. All approaches open to modern in vivo biological studies should be available to characterize and study cachexia. New animal models may be developed that would provide reproducible systems to study this process. It may also be possible to establish genetic, RNAi, TALEN, chemical biology, or other screening strategies to look for essential features of wasting and its regulation.
Implications of success: Advances in our knowledge about the causes and biology of cachexia will lead to better understanding of this late stage cancer event. Whether any of the causes or consequences of cachexia will be treatable remains unknown, but any advances will depend on intense study of its biology.
PQB - 4: What methods can be devised to characterize the functional state of individual cells within a solid tumor?
Background: Detailed tumor characterization through various omic-style studies revealed an unexpected degree of cell heterogeneity within each tumor. It now appears that each tumor is composed of a vast array of cells that have accumulated genetic and epigenetic changes during tumor development. Some of these changes are thought to be essential to key tumor properties, e.g., for cell survival, cell division, or range of therapeutic response, but others are almost certainly the so-called passenger changes that do not contribute to individual cell phenotype. Importantly, the array of different cells within the tumor contributes to functional heterogeneity as seen by enhanced evolution in response to changing selective pressures, escape from therapeutic interventions, and development of deadly metastatic potential. Methods to characterize cell functional heterogeneity have not been widely used to characterized the individual cells within solid tumors. We need to be able to identify and understand the features that promote further tumor development or therapeutic response. While methods to determine single cell phenotypes or genotypes are rapidly advancing and have been used to characterize single cells in culture and some blood tumors, it is essential to apply these methods to single cells within solid tumors. This Provocative Question seeks to stimulate technology advances of all types to depict and study the functional heterogeneity within solid tumors. Of note, this Provocative Question is limited to solid tumors and not blood tumors where cell separation and characterization methods already exist to study heterogeneity.
Feasibility: Major topics of current interest are new methods for in-depth analysis of single cells. Successful applications should feature some method of deep characterization of single cells combined with an approach to explore the features of single cells directly in a tumor, in tumor explants, or in cells isolated from solid tumors. It may be possible to study individual cells through in vivo imaging of the tumor in situ or in tumor explants to gain an understanding of tumor heterogeneity at a single-cell level. Another general approach might include the production of large panels of cell lines using newly developed immortalization strategies that would recapitulate the heterogeneity within one tumor. Isolation and single-cell cytometry may also be useful in some cases. The goal of successful applications should be to characterize individual tumor cells in sufficient detail that the features described through the single-cell analysis can be linked to functional phenotypes of whole tumor activities.
Implications of success: Understanding the functional heterogeneity of tumors provides fundamental knowledge that should lead to better understanding and predictions of tumor responses to any stress and to better understand the steps of tumor development. Methods developed in response to this question will push the technical abilities to find distinct functional subsets of tumor cells, and promise to greatly expand our capabilities of understanding the details of different cell phenotypes within a tumor.
Group C: Tumor Detection, Diagnosis, And Prognosis
PQC - 1: What properties of pre-cancerous lesions or their microenvironment predict the likelihood of progression to malignant disease?
Background: Not all tumors detected early should be treated. Uncertainty about the clinical behavior of a non-malignant lesion, such as the so-called “in situ carcinomas” of the prostate gland, esophagus, or breast, often lead to more aggressive treatment than may be warranted and can result in net harm to the patient. In addition, the inherent uncertainty in predicting the outcome of a given cancer, whether treated or not, can result in poor communication to the patient of the actual risk, leading to treatment decisions that may not be appropriate for the given benefit/risk profile. This Provocative Question seeks the identification of the characteristics of pre-cancerous lesions or their microenvironment that will allow the accurate prediction of progression to dangerous stages of tumor development.
Feasibility: Major advances in genomic and proteomic technologies that can genotype and phenotype small collections of cells and the microenvironment in which these cells proliferate, are resulting in a better understanding of how molecular profiles relate to cell phenotype and behavior. New knowledge will help determine whether malignant properties are conferred stochastically, or whether early lesions differ in their likelihood of malignant progression in definable and reproducible ways, thus allowing for more accurate prognostic determinants. Prospective studies could lead to substantial improvements in the accuracy with which the clinical behavior of a given lesion can be predicted.
Implications of success: Improved prediction of clinical risk could help clinicians better communicate risk/benefit profiles to patients and help patients, together with their doctors, make better-informed treatment decisions. Understanding which tumors are most likely to progress could also identify where therapeutic advances are most urgently needed. Insight into the biological basis for this stratification would be an important advance in the field, with broad relevance across organ sites. These changes could improve the overall benefit of early detection by reducing the risk of harm from overtreatment.
PQC - 2: What molecular or cellular events establish tumor dormancy after treatment and what leads to recurrence?
Background: Even apparently successful cancer therapy may leave or induce dormant tumors or other types of minimal residual disease. These dormant tumors may remain stable for decades and, in the best cases, will not present further danger to the patient. However, frequently these tumors may undergo changes that are poorly understood and become aggressive, dangerous lesions. This Provocative Question seeks a molecular understanding of how these dormant tumors are generated and, in addition, what might lead to their re-emergence as malignant tumors.
Feasibility: Perhaps the most difficult aspect of this question will be to identify a system where these dormant tumors can be studied in a reproducible manner. The use of mouse models may be possible or there may be types of human tumors that, when treated under specific regimens, frequently result in the appearance of dormant tumors. In these cases, it presumably will be the recurrent tumors arising from dormancy that will be available for careful study. These tumors could be profiled using modern biological methodologies to study potential similarities or differences.
Implications of success: This is a stage of tumor development that has been difficult to study to date, and, for that reason, we know very little about how these dormant tumors develop or why malignant variants eventually arise and cause tumor recurrence. Advances in methods to study these stages of tumor development and the characterization of the primary tumors for comparison will allow determination of how dormant tumors arise, how to detect these types of tumors after treatment, and which ones will be most important to follow.
PQC - 3: How do variations in tumor-associated immune responses among patients from distinct well-defined populations, such as various racial/ethnic or age groups, contribute to differences in cancer outcomes?
Background: There are clear disparities in cancer incidence and mortality rates found among diverse population groups, defined by race/ethnicity, age, or socio-economic status, that can be partially explained by differences in lifestyle and diet, age distribution, environmental and occupational exposure to carcinogens, or inadequate access to and affordability of health care. Some populations experience less favorable cancer outcomes compared to others. For example, African-American patients have a significantly greater risk of mortality due to prostate and breast cancer than their non-Hispanic white counterparts. Biological differences in genomics, gene expression and cellular immune response elements between diverse age, racial and ethnic populations have been previously reported. Variations among tumors and tumor-associated immunological differences between African-Americans and non-Hispanic whites and between older and younger patient populations have been implicated in cancer health disparities. Research is needed to validate these disparities in immune response and explore specific mechanisms and pathways that may explain these differences. Indeed, numerous differentially expressed genes have been reported to cluster around immune response and cytokine signaling pathways among patients from distinct well-defined populations such as various racial/ethnic, age groups, or groups afflicted with various co-morbid conditions. In turn these groups also experience unfavorable cancer outcomes. This Provocative Question seeks investigations that can functionally link immunological-related differences found among various well-defined populations to reduction of cancer health disparities.
Feasibility: Responsive applications to this PQ will include comparative studies to examine differences in immune response profiles between diverse populations. Demonstrated differences in immune signatures including immune cell infiltration, chemotaxis, and cytokine profiles, studies directed at characterization of immune response markers related to the tumor or with tumor-adjacent stroma as well as consequent cascade of events involving signal transduction and pathways differentially activated among diverse well-defined populations such as those defined by race/ethnicity or age could provide starting points for these studies. The goal of this work should be explain how these immune variations contribute to the aggressiveness or poor outcome of cancer in these populations.
Implications of success: It is expected that successful applications will lead to studies that will increase our understanding of the biological mechanisms that contribute to disparate cancer outcomes among diverse populations. Results from funded projects are expected to serve as a solid foundation for development of tangible strategies directed at eliminating these biologically-based sources of cancer outcome inequalities.
PQC - 4: What in vivo imaging methods can be developed to portray the "cytotype" of a tumor — defined as the identity, quantity, and location of each of the different cell types that make up a tumor and its microenvironment?
Background: Tumors are now understood to be complex multicellular units composed of a vast array of different tumor and host cells. The tumor and its microenvironment interact to influence how a tumor will evolve over time, how it will respond to therapeutic attack, and how dangerous it will be to the patient. This Provocative Question requires the development of sophisticated imaging methods to characterize this multicellular structure in order to predict how the microenvironment influences tumor behavior. There are many potential approaches to examining the tumor microenvironment, but one of the most valuable would be non-invasive imaging. An important step in developing such a characterization would be to determine the tumor “cytotype”. Here, we define the cytotype as the identity, quantity, and location of the different cells that make up a tumor and its microenvironment.
Feasibility: Building methods to record a tumor cytotype will come in stages. One avenue of development will need to focus on the careful identification of cell types within a tumor and its microenvironment. Specific probes that define subtypes of tumor cells or cells of its microenvironment will need to be established and verified. It seems reasonable that some investigators will concentrate on classes of cells in the tumor microenvironment. For example, a careful examination of tumor-infiltrating immune cells may be a reasonable approach. Another major avenue of work will tackle the quantitation and display of cells in 3-dimensional space, particularly with regard to their physical proximity to tumor cells, and the cellular architecture which might change over time. Some scientists may imagine methods to study differences in the tumor cells themselves. Carefully consideration of what types of tumors will be best suited for such studies and what tumor samples will be available for study is crucial. In some cases, mouse models may be better suited for reducibility and ease of sampling, but attention to how such methods will be adapted for human application is important. Since the imaging field is making rapid progress toward real time, in vivo monitoring of tumor phenotypes, the following question should be addressed: How will the characterization of tumor cytotypes be incorporated into this increasingly sophisticated view of the tumor in situ?
Implications of success: The ultimate goal this work will be to determine how different tumor cytotypes influence tumor behavior. Imaging methods that will identify different types of tumor architectures promise to improve all types of cancer diagnoses.
Group D: Cancer Therapy And Outcomes
PQD - 1: What molecular properties make some cancers curable with conventional chemotherapy?
Background: Although chemotherapy is often effective, it is rarely curative. However, it is well established that certain childhood cancers, some adult disseminated cancers, and rarely some adult solid tumors can be completely cured with chemotherapy, even with drugs that are often of much less value in other settings. While these responses are wonderful when they occur, there is little understanding of the underlying mechanisms that might explain why these cancers can be cured with chemotherapy. This Provocative Question seeks to understand what molecular properties of tumors make them curable by conventional chemotherapy.
Feasibility: This question has largely been ignored since it was recognized, decades ago, that such tumors could be cured by standard chemotherapeutic strategies. New methods are available for studying the biology of these “curable” cancers and for exploring the mechanisms by which the effective drugs work.
Implications of success: If we could identify the properties of cancers that render them susceptible to eradication by chemotherapy, we might better understand how certain therapies work, contemplate converting relatively insensitive tumors to highly sensitive ones, or develop new approaches to the treatment of intransigent malignancies.
PQD - 2: What features of standard-of-care therapies enhance or inhibit the efficacy of immunotherapy?
Background: Combining two or more therapies is one of the most common and effective methods to increase the effectiveness of cancer treatments. Looking for new combination therapies has become increasingly important as new targeted treatments have led to the generation of resistant tumors after continued therapy. Most approaches to test new combinations have relied on empirical assays that combine various small molecule inhibitors with one another or with chemotherapies. These approaches are being augmented by others that rely more deeply on rational strategies and use detailed knowledge of how different therapeutic outcomes can be best combined. Given the recent advances in the use immune modulatory therapies, i.e., those that rely on augmenting the ability of the host immune system to mount an immune response against the tumor such as stimulatory cytokines, activators of co-stimulatory molecules, immune checkpoint inhibitors, immune maturation agents, and therapeutic vaccines, the concept of combining these approaches with targeted or chemotherapy has begun to be considered and tested. However, we have little knowledge of how the results of current standard-of-care treatments for various malignancies will enhance or inhibit the addition of these immune modulatory therapies. This Provocative Question seeks to understand how best to combine these therapeutic approaches.
Feasibility: Any tumor model that shows a favorable response to an immune modulatory agent could be used to study how this response might be altered by other cancer therapeutic agents. We leave it to the ingenuity of applicants to choose how such agents might be selected for comparison. Any molecular events that are altered by potential agents could provide useful intermediate markers to measure collaborative effects that could predict changes in tumor response.
Implications of success: Extending the range of tumors that might respond to immune modulatory agents or the strength of their response may signal useful approaches that could be studied in subsequent clinical trials. More information about how any two agents enhance or inhibit one another will expand our understanding of the principles behind effective combination therapy.
PQD - 3: Do tumors evolve common features that could act as new therapeutic targets when they metastasize to the same secondary site?
Background: When tumors metastasize, their evolutionary development continues as they respond to the selective pressures at the sites of colonization. Recent studies have begun to catalog the molecular differences among different metastases that arise from the same primary tumor and variations seen between primary tumors and their metastases. How do the selective pressures of a specific metastatic environment influence each tumor’s development? Can common events be discerned among these changes? Such common events may be limited to metastases that arise from very similar origins or with very similar mutational histories. Alternatively, selective pressures of certain tissues might impose barriers that lead to very common solutions. Any common solutions, whether restricted to tumors of similar heritages or restricted to certain sites of metastasis, can be used to identify new targets for therapeutic attack.
Feasibility: As the molecular, cellular, and functional characterization of metastases increases, a vast amount of data will be available to examine for similarities. Similarities between metastases found at the same site could be based on any number of variables, including similar sites of primary tumor origin, similar sets of driver mutations, or similar local microenvironments. It is also possible that data from more than one set of variables may need to be aligned to allow similarities to become obvious.
Implications of success: Similar features would provide clues to identify a new class of potential targets for drug development.
PQD - 4: What are the mechanistic bases for differences in cancer drug metabolism and toxicity at various stages of life?
Background: It is well understood that patients process drugs in different ways at different stages of life. However, we know little about what accounts for these differences. How does liver or kidney enzymology change as patients age? What molecular changes in drug uptake and metabolism can be rigorously determined and can we use these changes to understand how to adjust therapeutic decisions, adjust doses, or change regimens to better link cancer therapies to patient age?
Feasibility: Drug metabolism studies have not yet linked findings to the various physiological differences associated with aging. The same methods currently used in cancer drug metabolism studies could be combined with our growing understanding of the molecular changes detected in aging individuals. Similar strategies could be used to understand other differences related to patients’ ages.
Implications of success: The definition of key steps in drug metabolism that change with age could lead to simple tests to measure these responses and then better tailor drug delivery to cancer patients at their actual stage of life.
Group E: Clinical Effectiveness
PQE - 1: What strategies optimize adoption and sustainability of guideline concordant cancer treatments in community settings?
Background: Advances in establishing best cancer treatments are painstakingly developed through a well-established and rigorous clinical trials process. Getting these treatments to be widely used and well accepted by the entire community is a complicated process that can be inhibited by many social, economic, and cultural barriers. Some of the many barriers to rapid dissemination include: patients who participate in clinical trials are often younger and much healthier than the most common cancer patients seen in community practice, the site of the trial (e.g., frequently only at academic medical centers or comprehensive cancer centers), or lack of engagement of community practice in the design of the trial (e.g., requires equipment not typically available in office-based practice). However, little research has been conducted on innovative approaches to improve the uptake of guideline related cancer care, particularly in the area of cancer treatment. In cancer screening and in other fields a number of approaches less commonly used in medical practice, such as behavioral economics, systems and industrial engineering, the use of social media, and real-time data sharing across multidisciplinary teams working on common problems, has led to innovative approaches that hasten adoption and may improve sustainability of recommended care. This Provocative Question seeks to understand which methods for adoption of new treatment strategies work most effectively and determine how these methods can be employed more widely.
Feasibility: Investigators are beginning to explore the use of these innovations that have been successful at implementing and sustaining change in non-medical arenas. Some clinicians, health services researchers, and health information innovators have been piloting some of these approaches in medical care.
Implications of success: Exploration of how these diverse approaches to interventions can improve guidelines concordant cancer care could have substantial influence at a time when the US health care system is evolving rapidly under the affordable care act. These innovations could lead to much more rapid uptake of research results, resulting in higher quality, more effective care for less cost.
PQE - 2: What care delivery models can be developed to transition cancer patients effectively from active therapy to end of life care?
Background: National research has documented that cancer treatment costs are especially high and remain focused on tumor remission with limited attention to palliation or quality of life in the end-of-life phase for patients with advanced stage or recurrent cancer. Evidence for treatment effectiveness is also not definitive in this domain and yet research suggests that patients and their providers often believe that treatment in this phase will “cure” their cancer. However, recent research has suggested that alternative approaches to clinical care that include shared decision making and early communication about the goals of clinical care during all of the phases of care rather than delaying until the end of life may more effectively help patients and their clinicians to transition from active therapy to end of life care. Use of multidisciplinary teams of clinicians, interactive patient reported outcomes information systems and other approaches may help guide the selection of care that is more effective and appropriate to the phase of a cancer patient’s course.
Feasibility: Recent IOM and other reports have characterized the necessary components of cancer care planning and many cancer-related professional societies have begun discussion on how to incorporate such care planning into practice. Innovations in shared decision making, decision analysis, team science and advances in communication and interactive technologies should greatly advance this field of research.
Implications of success: Research on how to effectively transition providers, patients, and their care takers from active treatment to end of life care will enhance the quality of life of cancer patients, ensure that care during this period of life is appropriate to patients needs and will reduce the cost and adverse effects of active cancer treatment that is unlikely to benefit patients in this phase of their life. Furthermore, it is likely to advance the use of palliative and symptom management care earlier in a patient’s cancer treatment, which may have further benefit.
PQE - 3: What methods and approaches induce physicians and health systems to abandon ineffective interventions or discourage adoption of unproven interventions?
Background: It is common for community hospitals and community cancer centers to acquire high cost technology or other cutting edge therapies as a way of differentiating their services in local markets. Examples include cyber knife and robotic surgery as well as a variety of new radiation services such as PET scans. Often these technologies require specialized clinicians experienced in their use. Once these technologies are purchased, there is considerable pressure to maximize their use for clinical applications, including cancer diagnosis and treatment, to recover investment capital. However, a number of these technologies are unproven as they have not been studied to evaluate whether their use improves patients’ outcomes. Furthermore, little is known about the influence of introduction of these technologies on cancer care costs and outcomes, including their comparative effectiveness with more established, and often lower cost, treatment alternatives. Innovations in comparative effectiveness, decision analysis and other approaches can quantify both the short and long terms costs and benefits of premature adoption of such technologies.
Feasibility: The expansion of comparative effectiveness research, decision analysis, and other modeling approaches has been used extensively in the field of cancer screening. These approaches have been minimally applied to new technologies in the area of cancer treatment but could be readily adapted to cancer treatment.
Implications of success: Innovative approaches to providing such information to physicians, health care systems and health care administrators may help guide better quality decisions and improve patient care and outcomes.
PQE - 4: What are the best methods to identify and stratify subgroups of patients with particular co-morbidities who will benefit from defined cancer therapies?
Background: Existing clinical trial results are limited to individuals who have few if any co-morbidities. Yet, most cancer patients in the US are over age 65 and often have comorbid conditions that may complicate decisions related to optimal cancer therapies for these patients. In addition, many patients who would be candidates for new therapies may have complex comorbid disease. What are the circumstances in which comorbidities may be a problem with specific therapies and what should clinicians do in assessing the appropriateness of a therapy for patients whose clinical profile do not match trial eligibility criteria?
Feasibility: The existence of large, integrated clinical databases of cancer patients with data on their comorbid conditions, genetic, laboratory and pharmaceutical measures for assessing severity of disease combined with complex statistical and other mathematical modeling approaches enables multi-disciplinary teams of investigators to develop prediction models of anticipated outcomes given diverse clinical and treatment scenarios. These resources allow the validation of predicted models against actual outcomes in patients and the ability to assess if this approach can be used for multiple different cancers and patients with diverse combinations of comorbid disease.
Implications of success: Successful approaches that have been validated in selected patient populations with specific comorbid disease and end organ effects could be applied more broadly to a wide range of cancer patients. The ability to tailor treatment in this way should allow patients with complex medical conditions to maximally benefit from advances in cancer therapy and to avoid adverse complications of that therapy.