Search results for: prognostic-factors-in-cancer

Prognostic Factors in Cancer

Author : Paul Hermanek
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M. K. Gospodarowicz, P. Hermanek, and D. E. Henson Attention to innovations in cancer treatment has tended to eclipse the importance of prognostic assessment. However, the recognition that prognostic factors often have a greater impact on outcome than available therapies and the proliferation of biochemical, molecular, and genetic markers have resulted in renewed interest in this field. The outcome in patients with cancer is determined by a combination of numerous factors. Presently, the most widely recognized are the extent of disease, histologic type of tumor, and treatment. It has been known for some time that additional factors also influence outcome. These include histologic grade, lymphatic or vascular invasion, mitotic index, performance status, symptoms, and most recently genetic and biochemical markers. It is the aim of this volume to compile those prognostic factors that have emerged as important determinants of outcome for tumors at various sites. This compilation represents the first phase of a more extensive process to integrate all prognostic factors in cancer to further enhance the prediction of outcome following treatment. Certain issues surround ing the assessment and reporting of prognostic factors are also considered. Importance of Prognostic Factors Prognostic factors in cancer often have an immense influence on outcome, while treatment often has a much weaker effect. For example, the influence of the presence of lymph node involvement on survival of patients with metastatic breast cancer is much greater than the effect of adjuvant treatment with tamoxifen in the same group of patients [5].

Prognostic Factors in Cancer

Author : International Union against Cancer
File Size : 73.58 MB
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Prognostic Factors in Cancer, Second Edition updates the first authoritative monograph on prognostic factors and their use in planning treatment for cancer patients. The text is an extension of the work of the International Union Against Cancer (UICC) on the TNM Classification of Malignant Tumours and their current focus on prognostic factors in cancer. The TNM classification is the most widely used system for staging the progression of cancer. The anatomic extent of disease represented by the TNM system is the single most important predictor for outcomes of most tumors. Prognostic Factors in Cancer, Second Edition is divided into two parts. The first section examines prognosis in general and more specifically prognosis in cancer patients, including issues surrounding accuracy of measurement of prognosis, the methodology of studying and classifying prognostic factors, and the application of prognostic factors in clinical decision-making in the treatment of cancer. The second section provides chapters on site-specific or tumor-specific neoplasms and the prognostic factors associated with them. These chapters contain an overview of the relevant literature and include summaries that classify prognostic factors according to subject and relevance. Prognostic Factors in Cancer, Second Edition illustrates the scope of the field as it stands today, and will provide perspective on likely outcomes of neoplastic disease for all physicians and others responsible for the care of patients with cancer.

Prognostic Factors in Cancer Second Edition

Author : Gospodarowicz
File Size : 26.30 MB
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Prognostic Factors in Cancer

Author : Clinical Ligand Assay Society (U.S.)
File Size : 47.62 MB
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Prognostic Factors in Breast Cancer

Author : C. J. Davies
File Size : 63.3 MB
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Cancer Therapy

Author : Maurice J. Staquet
File Size : 54.47 MB
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Incidence Life Expectancy and Prognostic Factors of Cancer Patients Under Prolonged Mechanical Ventilation

Author : 施至遠
File Size : 72.2 MB
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Cancer Therapy

Author : Maurice J. Staquet
File Size : 50.96 MB
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Patient Centered Prognosis

Author : Miller III, Kashani-Sabet, & Sagebiel
File Size : 21.37 MB
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Patient-centered prognosis focuses on individual patients. It is a methodology that generates individually tailored probabilistic predictions of a specified medical outcome that a particular patient may experience. Its predictions are based on observable 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 current prognostic practice. PCM achieves its greater predictive accuracy by exploiting several analytical devices. 1. It redesigns and retools each successive stage of the prognostic 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 prognostic factor’s relationship to the particular outcome as that relationship pertains, specifically, to patients similar to the targeted patient. 3. It relies on internal interrelationships among different prognostic factors and the specified outcome to “fill in” missing observations so that an individually tailored probabilistic prediction is possible, even with incomplete patient data. PCM is applied to 1,222 melanoma patients from the United States and to 1,225 patients from Finland with invasive breast cancer. Substantial improvements in prognostic accuracy are realized in both applications compared to current prognostic practice. Greater accuracy can lead to better treatment selection decisions and to other improvements in patient management. Greater prognostic accuracy can also eliminate unnecessary medical procedures that are frequently both painful and expensive in treating progressive diseases such as cancer.

Prognostic Factors in Gastric Cancer

Author : Ilfet Songun
File Size : 26.88 MB
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