Understanding how a disease and its associated health care interventions affect the lives of individuals is important whatever the medical condition, but especially so for diseases that are chronic or incurable and for which treatments often have toxic and long-lasting consequences. For this reason, cancer provides an exceptionally compelling model for examining the impact of disease on individual well-being. It is the second leading cause of death in the US, with one out of every four deaths in 2004 (over 560 000 in total) projected to be attributable to cancer. Many more individuals (an estimated 9.6 million in 2000) will be undergoing cancer treatment, coping with progressive disease, or living cancer-free in the aftermath of diagnosis and treatment.

The principal means of treating cancer — surgery, chemotherapy, and radiation — are powerful and toxic. All of these treatments, and additional ones like hormonal therapy, have side effects, which may be short-term or time-limited, or chronic and persistent, or else generate late effects emerging only after treatment is completed and sometimes not evident until many years later. Efforts to prevent, screen for, and treat cancer are all aimed at maximizing the chances for a healthy life while, at the same time, minimizing the associated side effects. In addition to its mortality and morbidity impact, cancer inflicts an enormous economic burden on society.

Introduction

The perspectives of individuals who receive cancer-related interventions provide important information about diagnosis, treatment, and continuing care. These patient-centered data also have implications for the effectiveness of interventions and the quality of cancer care and can thus be an important resource for decision makers who deliver, pay for, regulate, and evaluate cancer care. At the same time, measuring such outcomes poses challenges different from those of biomedical outcomes. In particular, certain patient-centered outcomes (e.g., health-related quality of life) are subjective, by design, and not directly verifiable by physiological or other objective indicators, while others (e.g., economic outcomes) are not generally part of standard clinical information systems. Because of the growing importance of outcomes data, the National Cancer Institute (NCI) convened the Cancer Outcomes Measurement Working Group (COMWG) to assess the current state of the science and to provide recommendations for future research to improve the field. This book reports on findings from the COMWG effort.

The COMWG focused on three primary outcomes — health-related quality of life (HRQOL), patient needs and satisfaction, and economic burden — in the four cancers that affect the largest numbers of individuals in the USA: breast, colorectal, lung, and prostate. The group also considered outcomes measurement across the entire spectrum of cancer prevention, treatment, survivorship, and end-of-life care. COMWG members provided critical review and discussion of current literature in specified topics, as well as identification of areas where more work is needed.

Introduction

It is clear from earlier chapters that data for measuring, interpreting, explaining, and predicting cancer outcomes are currently available from a variety of sources. Cancer registries, medical records, administrative claims data, and patient and provider surveys yield, individually or in concert, information about a range of outcomes that matter to decision makers. These outcomes include not only survival, disease-free survival, tumor progression, and a host of other biomedical endpoints, but important patient-reported outcomes that are the focus of this book — health-related quality of life (HRQOL), patient perceptions of and satisfaction with care, and the economic burden of cancer and its treatment. Moreover, these same data sources also yield, with varying degrees of completeness, information on a variety of factors associated with variations in cancer outcomes. These include socioeconomic and other demographic descriptors, comorbidities and other clinical determinants, and provider and health system variables.

At the moment, no single database or system provides sufficiently comprehensive information on the full range of variables required for cancer outcomes research. Rather, what we have is a substantial number of public agencies and private organizations doing an increasingly good job at collecting important pieces, components, and parts of the data required for the cancer outcomes research agenda of today and tomorrow.

In the immediate future and beyond, new prevention, diagnostic, treatment, and palliative modalities will continue to emerge. Public and private payment systems will continue to evolve, as pressures for both cost containment and quality assurance grow.