Method for diagnosing and treating breast cancer
First Claim
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1. A method of evaluating an expected time to recurrence of a breast cancer in a patient, the method comprising the steps of:
- (a) providing numerical data for a plurality of observed times to recurrence and an associated plurality of nuclear pleomorphic features comprising;
radius;
texture;
perimeter;
area;
smoothness;
compactness;
concavity;
concave points;
symmetry; and
fractal dimension;
(b) performing a nonlinear regression on the numerical data to select a coefficient for each of the plurality of nuclear pleomorphic features, such that the selected coefficients provide a local extreme in the correlation to the corresponding times to recurrence;
(c) measuring at least two of the plurality of nuclear pleomorphic features in tumor tissue of the patient; and
(d) calculating a prognostic index by multiplying each of the at least two measured pleomorphic features in tumor tissue of the patient by the corresponding coefficients selected in step (b).
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Abstract
A method of evaluating progress of a cancer comprises calculating a prognostic index by selecting coefficients for each of a plurality of nuclear pleomorphic features using a numerical regression, such that the selected coefficients provide a correlation extremum to times to recurrence. A prognostic index is calculated by measuring nuclear pleomorphic features in a patient, and multiplying the observed values by the corresponding selected coefficients. The resulting prognostic index can provide a superior prediction of the likely time to recurrence in the patient.
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1 Claim
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1. A method of evaluating an expected time to recurrence of a breast cancer in a patient, the method comprising the steps of:
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(a) providing numerical data for a plurality of observed times to recurrence and an associated plurality of nuclear pleomorphic features comprising;
radius;
texture;
perimeter;
area;
smoothness;
compactness;
concavity;
concave points;
symmetry; and
fractal dimension;
(b) performing a nonlinear regression on the numerical data to select a coefficient for each of the plurality of nuclear pleomorphic features, such that the selected coefficients provide a local extreme in the correlation to the corresponding times to recurrence;
(c) measuring at least two of the plurality of nuclear pleomorphic features in tumor tissue of the patient; and
(d) calculating a prognostic index by multiplying each of the at least two measured pleomorphic features in tumor tissue of the patient by the corresponding coefficients selected in step (b).
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Specification