Surgery – Diagnostic testing
Reexamination Certificate
2000-01-10
2001-10-23
Jaworski, Francis J. (Department: 3737)
Surgery
Diagnostic testing
C128S924000
Reexamination Certificate
active
06306087
ABSTRACT:
TECHNICAL FIELD
The present invention relates to methods for diagnosing, screening or prognosing diseases. More particularly, the present invention relates to a method for diagnosing, screening or prognosing diseases in humans or animals, and for determining the severity and cause of the disease.
The present invention further relates to a computer assisted method for diagnosing, screening or prognosing diseases, utilizing one or multiple neural networks to obtain a diagnostic index. In preferred embodiments of the present invention, the method is used to diagnose, and prognose diseases such as osteoporosis and cancers, including but not limited to ovarian, breast, testicular, colon and prostate cancer. In another preferred embodiment, the invention includes a system to receive patient data transmitted from data transmitting stations, to process these data through the trained neural networks to produce a diagnostic value or prognostic value, and to transmit these values to a remote data receiving means.
BACKGROUND OF THE INVENTION
As used herein, the term “disease” is defined as a deviation from the normal structure or function of any part, organ or system of the body (or any combination thereof). A specific disease is manifested by characteristic symptoms and signs, including both chemical and physical changes. A disease is-often associated with a variety of other factors including but not limited to demographic, environmental, employment, genetic and medically historical factors. Certain characteristic signs, symptoms, and related factors can be quantitated through a variety of methods to yield important diagnostic information. For purposes of this application, the quantifiable signs, symptoms and/or analytes in biological fluids characteristic of a particular disease are defined as “biomarkers” for the disease. Current diagnostic and prognostic methods depend on the identification and evaluation of these biomarkers, both individually and as they relate to one another. Often the diagnosis of a particular disease involves the subjective analysis by a clinician, such as a physician, veterinarian, or other health care provider, of the data obtained from the measurement of the factors mentioned above in conjunction with a consideration of many of the traditionally less quantitative factors such as employment history. Unfortunately, this subjective process of diagnosing or prognosing a disease usually cannot accommodate all the potentially relevant factors and provide an accurate weighting of their contribution to a correct diagnosis or prognosis.
Generally, the pathological process involves gradual changes that become apparent only when overt change has occurred. In many instances, pathological changes involve subtle alterations in multiple biomarkers. It is uncommon that a single biomarker will be indicative of the presence or absence of a disease. It is the pattern of those biomarkers relative to one another and relative to a normal reference range, that is indicative of the presence of a disease. Additional factors including but not limited to demographic, environmental, employment, genetic and medically historical factors may contribute significantly to the diagnosis or prognosis of a disease, especially when considered in conjunction with patterns of biomarkers. Unfortunately, the subjective diagnostic process of considering the multiple factors associated with the cause or presence of a disease is somewhat imprecise and many factors that may contribute significantly are not afforded sufficient weight or considered at all.
When individual biomarkers do not show a predictable change and the patterns and interrelationships among the biomarkers viewed collectively are not clear, the accuracy of a physician's diagnosis is significantly reduced. Also, as the number of biomarkers and demographic variables relevant for the diagnosis of a particular disease increases, the number of relevant diagnostic patterns among these variables increases. This increasing complexity decreases the clinician's ability to recognize patterns and accurately diagnose or predict disease.
Prostate cancer affects numerous individuals each year and many of them are killed by the disease. The early and accurate diagnosis of prostate cancer has been very difficult to achieve with reliability and accuracy. However, early diagnosis of prostate cancer is essential to maximizing the possibility of successfully treating the disease. Current screening techniques include digital rectal examination (DRE), transurethral prostatic biopsy, and measurement of prostate specific antigen (PSA) in the blood. Reliance on serum PSA levels, especially low PSA levels, as a sole diagnostic measure of prostate cancer often provides unacceptable levels of inaccurate diagnosis. These screening techniques miss many cases of early stage prostate cancer resulting in growth of the cancer within the prostate gland and also outside the capsule of the gland. It is essential to diagnose this disease in the early stages, well before metastases have occurred.
In addition, diagnostic methods should be capable of distinguishing between benign prostatic hyperplasia (BPH) and prostate cancer and to distinguish between cases of cancer and non-cancer. What is also needed is a valid, reliable, sensitive and accurate technique that can diagnose or prognose prostate cancer at an early stage and also distinguish the various stages of prostate cancer which can be characterized as T1b, T2, T3 and TNxM1.
Osteoporosis and osteopenia provide another example of disease with multiple biomarkers, the following biomarkers collectively show characteristic changes in the presence of osteoporosis: calcium, phosphate, estradiol (follicular, mid-cycle, luteal, or post-menopausal), progesterone (follicular, mid-cycle, luteal, mid-luteal, oral contraceptive, or over 60 years), alkaline phosphatase, percent liver-ALP, and total intestinal-ALP. After measuring these biomarkers, a diagnosing clinician would next compare the measurements to a normal reference range. While some of the biomarkers may fall outside the normal reference range, others may fall clearly within the normal reference range. In some circumstances, all of the biomarker values may fall within a normal reference range. Presented with such data, a clinician may suspect that a patient has undergone some bone loss, but will be unable to reach a conclusive and meaningful diagnosis as to the presence of the disease osteoporosis.
The characteristic changes in biomarkers associated with some diseases are well documented; however, the quantitative interpretation of each particular biomarker in diagnosing a disease and determining a prognosis is not well established. The difficulties inherent in formulating a diagnosis from the analysis of a set of laboratory data is best illustrated by looking closer at conventional diagnostic methods for a specific disease. A discussion of the disease osteoporosis follows.
The term “osteopenia” as used herein means any decrease in bone mass below the normal. The term “osteoporosis” as used herein means a specific form of generalized osteopenia characterized by a decrease in bone density, low bone mass, and microarchitectural deterioration of bone tissue.
Osteopenia encompasses a group of diseases with diverse etiologies typified by reduction in bone mass per unit volume to a level below that which is necessary for adequate mechanical support. Osteoporosis is the result of the gradual depletion of the inorganic portion of the skeleton and can be caused by any number of factors. Primary osteoporosis is an age related disorder that is particularly common in women and is characterized by decreased bone mass in the absence of other recognizable causes. However, osteoporosis occurs in both men and women. In women it is recognized usually at the 5
th
or 6
th
decade, following menopause. In men osteoporosis is often recognized around their 6
th
or 7
th
decade of life.
Several demographic parameters are associated with enhanced risk of developing osteoporosis. The follo
Barnhill Stephen D.
Zhang Zhen
Horus Therapeutics, Inc.
Jaworski Francis J.
Kilpatrick & Stockton LLP
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