Patient-Centered Diagnosis

About the Book

Patient-centered diagnosis and prognosis focus on individual patients. Both rely on a methodology that generates individually tailored probabilistic predictions of a specified medical outcome that a particular patient may experience. Predictions are based on observable diagnostic and prognostic factors. Because these predictions are both particular-outcome-specific and individual-patient-specific, achieving predictive accuracy poses a formidable challenge. Nevertheless, the patient-centered methodology (PCM) appears to produce more accurate individually tailored patient predictions than those typically achieved under current medical practice.

PCM achieves its greater predictive accuracy by exploiting several analytical devices.

1. It redesigns and retools each successive stage of the analytical procedure to predict the particular future outcome that the targeted patient could experience.

2. It identifies the existence, the direction, the shape, and the magnitude of each diagnostic and prognostic factor’s relationship to the particular outcome as that relationship pertains, specifically, to patients similar to the targeted patient.

3. It relies on detected interrelationships among separate diagnostic and prognostic factors and between both and the specified outcome to “fill in” missing observations so that an individually tailored probabilistic prediction is possible, even with incomplete patient data.

From a physician’s perspective, greater accuracy can facilitate better treatment selection choices and other improvements in patient management. From a patient’s perspective, greater accuracy can facilitate more appropriate future planning and lifestyle choices.

These benefits are illustrated by applying PCM to two diagnostic tests currently offered to cancer patients (sentinel lymph node biopsies and FDG-PET/CT scans) and to a novel diagnostic procedure (DSSA) recently developed to distinguish malignant melanomas from benign nevi (ordinary moles). PCM appears capable of reducing the cost of these current diagnostic tests by at least 40 percent and of increasing their triage efficiency by at least 66 percent. PCM, when incorporated within DSSA, also appears capable of achieving a sensitivity of 97 percent, a specificity of 98 percent, and a correct discrimination rate of 97 percent in distinguishing malignant melanomas from benign nevi.

About the Author

For more than thirty years James R. Miller III, PhD, was a professor at the Stanford Graduate School of Business. He has been doing full-time cancer research since his retirement in 1997 as Walter and Elise Haas Professor of Business Administration. He received a Bachelor's Degree from Princeton University, a Woodrow Wilson Fellowship (University of California at Berkeley), an MBA from the Harvard Business School, and a PhD from the Massachusetts Institute of Technology. He has previously published two books and more than 45 monographs and articles in professional journals. Professor Miller is the inventor of six United States software patents. He has served on more than a dozen boards of directors in the United States and Europe and as CEO of two start-up companies in the Silicon Valley. He has three daughters and six grandchildren.

Mohammed Kashani-Sabet, MD, is Medical Director of Cancer Programs at the California Pacific Medical Center (CPMC). He also serves as Director of the Center for Melanoma Research and Treatment and Senior Scientist at the CPMC Research Institute. Dr. Kashani-Sabet earned his medical degree from the State University of New York at Stony Brook, where he also completed an internship in internal medicine. He then completed a residency in dermatology at the University of California at San Francisco (UCSF), as well as a post-doctoral fellowship in cutaneous oncology, and received training in both dermatology and medical oncology. Dr. Kashani-Sabet maintains clinical interests in melanoma and cutaneous lymphoma and research interests in targeted therapy, ribozymes, siRNAs, tumor metastasis, prognostic factors, and tumor biomarkers for both diagnosis and prognosis.

Richard W. Sagebiel, MD, was born in Ohio in 1934. He received his Bachelor's Degree from Yale University in 1956 in Music and Literature. He did his medical studies at the Harvard Medical School, including a year of pathology and research between his second and third years at the Massachusetts General Hospital (MGH). After an intern year of general medicine he returned to MGH to study detmatopathology with Wallace H. Clark, MD. He completed his training in the Departments of Dermatology and Pathology at the University of Washington Medical School. In 1970 he joined the Clinical Faculty of the University of California at San Francisco (UCSF), working with M. Scott Blois, PhD, MD, and others to form a Clinical Cooperative Melanoma Group. This group included Drs. Clark, Fitzpatrick (Harvard), and Kopf (NYU). It stimulated the creation of similar melanoma groups throughout the country. From 1988 to 1998 Dr. Sagebiel was Director of the UCSF Melanoma Clinic. He then retired and became a Consulting Pathologist to that clinic and, later, to the CPMC Center for Melanoma Research and Treatment.