Global Journal of Cancer Therapy

Journal Information
EISSN : 2581-5407
Published by: Peertechz Publications Inc. (10.17352)
Total articles ≅ 44
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Wu Jianqing, Zha Ping
Global Journal of Cancer Therapy, Volume 8, pp 021-033; https://doi.org/10.17352/2581-5407.000044

Abstract:
Chronic diseases are still known as incurable diseases, and we suspect that the medical research model is unfit for characterizing chronic diseases. In this study, we examined accuracy and reliability required for characterizing chronic diseases, reviewed implied presumptions in clinical trials and assumptions used in statistical analysis, examined sources of variances normally encountered in clinical trials, and conducted numeric simulations by using hypothetical data for several theoretical and hypothetical models. We found that the sources of variances attributable to personal differences in clinical trials can distort hypothesis test outcomes, that clinical trials introduce too many errors and too many inaccuracies that tend to hide weak and slow-delivering effects of treatments, and that the means of treatments used in statistical analysis have little or no relevance to specific patients. We further found that a large number of uncontrolled co-causal or interfering factors normally seen in human beings can greatly enlarge the means and the variances or experimental errors, and the use of high rejection criteria (e.g., small p values) further raises the chances of failing to find treatment effects. As a whole, we concluded that the research model using clinical trials is wrong on multiple grounds under any of our realistic theoretical and hypothetical models, and that misuse of statistical analysis is most probably responsible for failure to identify treatment effects for chronic diseases and failure to detect harmful effects of toxic substances in the environment. We proposed alternative experimental models involving the use of single-person or mini optimization trials for studying low-risk weak treatments.
Wu Jianqing, Zha Ping
Global Journal of Cancer Therapy, Volume 8, pp 046-049; https://doi.org/10.17352/2581-5407.000043

Abstract:
Medicine fails to find predictable cures for cancer in more than a century, and we explored the feasibility of controlling cancer growth speed by using lifestyle factors. After conducting an extensive literature review, we conducted simulations for cancer growth courses to see the feasibility of controlling cancer growth speeds. We found that (1) medical treatments are often accompanied by three to four lethal factors: treatment side-effects, emotional distress, and chronic stress, reduced exercises and physical inactivity, and excessive nutrition in some cases; (2) clinical trial exaggerates treatments short-term benefits 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 comparisons, where surgery may work as a negative standard relative to the best alternatives for resolving cancer; (4) the strategy of destroying the tumor or killing all cancer cells is unworkable; (5) medical treatments can turn natural cancer growth curve into approximately doubly exponential curve; (6) multiple-factor non-medical measures are potentially much more powerful than medical treatments in controlling cancer growth and metastasis speeds; and (7) cancer early diagnosis and over treatments are unwise strategies in light of discoveries. Based on huge increases in cancer growth rate constants, substantial loss of vital organ functional capacity, and severe systemic aging-like cellular damages, we concluded that medical treatments may promote cancer growth and metastasis speeds and shorten patient lives in most situations, and the claimed benefits are caused by triple biases of clinical trials. By using the same method to explore how several lifestyle factors affect cancer growth rates, we concluded that the better strategy for ending the global cancer epidemic in the future is changing caner treatment strategy from killing cancer cells to slowing down cancer growth rates by using various lifestyle factors in combination. This study in part explains why cancer can self-resolve.
, Gonzalez Barcena Jose Miguel, Martin Yuranis Garciga, Morales Yahumara Suarez
Published: 10 November 2020
Global Journal of Cancer Therapy, Volume 6, pp 042-044; https://doi.org/10.17352/2581-5407.000035

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