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Surgery, Chemotherapy and Radiotherapy Promote Cancer Growth Speeds and Shorten Patient Lives
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Submitted:
21 November 2019
Posted:
24 November 2019
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Abstract
After reviewing cancer theories, cancer treatment development histories, randomized clinical trial's performance, cancer treatment strategy, trial follow-up times, and conducting numerous simulations using existing data, the authors found: (1) medical treatments come with three to four lethal factors: treatment side-effects, emotional distress and chronic dress, lack of exercises or physical inactivity, and excessive nutrition in some cases; (2) clinical trial exaggerates the benefits of fast-acting treatments and underestimates the slow-delivering adverse side effects as a result of statistical averaging, interfering effects of personal lifestyle factors, and insufficient follow-up times; (3) the benefits of medical treatments are limited by chain comparison, where surgery sets up a negative standard relative to the best way for resolving cancer; (4) the strategy of destroying the tumor is unworkable; (5) medical treatments can turn natural cancer growth curve into approximately doubly exponential curve; (6) multiple factor non-medical measures are much more powerful than medical treatments in controlling cancer growth and metastasis rates; and (7) cancer early diagnosis and over treatments are bad strategies that have great adverse impacts on cancer patients. Based on huge increases in cancer growth rate constants, substantial of loss of organ functional capacity, and severe systemic aging-like cellular damages, the authors concluded that medical treatments promote cancer growth and metastasis rates and shorten patient lives in most cases, and the claimed benefits are caused by triple biases of clinical trials. The authors believe that the better strategy for ending the global cancer epidemic is abandoning clinical trails as the research model, changing caner treatment strategy from killing cancer cells to slowing down cancer growth rates by using multiple factors optimization approach in personalized medicine.
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Subject: Medicine and Pharmacology - Oncology and Oncogenics
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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