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Journal articles on the topic 'Dose response relationships'

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Published: 4 June 2021

Last updated: 20 February 2023

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1

May, Susanne, and Carol Bigelow. "Modeling Nonlinear Dose-Response Relationships in Epidemiologic Studies: Statistical Approaches and Practical Challenges." Dose-Response 3, no. 4 (October 1, 2005): dose—response.0. http://dx.doi.org/10.2203/dose-response.003.04.004.

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Non-linear dose response relationships pose statistical challenges for their discovery. Even when an initial linear approximation is followed by other approaches, the results may be misleading and, possibly, preclude altogether the discovery of the nonlinear relationship under investigation. We review a variety of straightforward statistical approaches for detecting nonlinear relationships and discuss several factors that hinder their detection. Our specific context is that of epidemiologic studies of exposure-outcome associations and we focus on threshold and J-effect dose response relationships. The examples presented reveal that no single approach is universally appropriate; rather, these (and possibly other) nonlinearities require for their discovery a variety of both graphical and numeric techniques.

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2

Lieberman, Ronald, and Robert Nelson. "Dose-Response and Concentration—Response Relationships." Therapeutic Drug Monitoring 15, no. 6 (December 1993): 498–502. http://dx.doi.org/10.1097/00007691-199312000-00008.

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3

Glines, Wayne M. "Models of Dose Response Relationships." Health Physics 118, no. 3 (March 2020): 281–86. http://dx.doi.org/10.1097/hp.0000000000001190.

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4

Swenberg, James A., David K. La, Nova A. Scheller, and Kuen-yuh Wu. "Dose-response relationships for carcinogens." Toxicology Letters 82-83 (December 1995): 751–56. http://dx.doi.org/10.1016/0378-4274(95)03593-1.

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5

Scott, Bobby R. "Stochastic Thresholds: A Novel Explanation of Nonlinear Dose-Response Relationships for Stochastic Radiobiological Effects." Dose-Response 3, no. 4 (October 1, 2005): dose—response.0. http://dx.doi.org/10.2203/dose-response.003.04.009.

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New research data for low-dose, low- linear energy transfer (LET) radiation-induced, stochastic effects (mutations and neoplastic transformations) are modeled using the recently published NEOTRANS3 model. The model incorporates a protective, stochastic threshold (StoThresh) at low doses for activating cooperative protective processes considered to include presumptive p53-dependent, high-fidelity repair of nuclear DNA damage in competition with presumptive p53-dependent apoptosis and a novel presumptive p53-independent protective apoptosis mediated (PAM) process which selectively removes genomically compromised cells (mutants, neoplastic transformants, micronucleated cells, etc.). The protective StoThresh are considered to fall in a relatively narrow low-dose zone (Transition Zone A). Below Transition Zone A is the ultra-low-dose region where it is assumed that only low-fidelity DNA repair is activated along with presumably apoptosis. For this zone there is evidence for an increase in mutations with increases in dose. Just above Transition Zone A, a Zone of Maximal Protection (suppression of stochastic effects) arises and is attributed to maximal cooperation of high-fidelity, DNA repair/apoptosis and the PAM process. The width of the Zone of Maximal Protection depends on low-LET radiation dose rate and appears to depend on photon radiation energy. Just above the Zone of Maximal Protection is Transition Zone B, where deleterious StoThresh for preventing the PAM process fall. Just above Transition Zone B is a zone of moderate doses where complete inhibition of the PAM process appears to occur. However, for both Transition Zone B and the zone of complete inhibition of the PAM process, high-fidelity DNA repair/apoptosis are presumed to still operate. The indicated protective and deleterious StoThresh lead to nonlinear, hormetic-type dose-response relationships for low-LET radiation-induced mutations, neoplastic transformation and, presumably, also for cancer.

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6

Iavicoli, Ivo, Giovanni Carelli, and Alessandro Marinaccio. "Dose-Response Relationships in Human Experimental Exposure to Solvents." Dose-Response 4, no. 2 (April 2006): dose—response.0. http://dx.doi.org/10.2203/dose-response.05-036.iavicoli.

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7

van Wijngaarden, Edwin. "A Graphical Method to Evaluate Exposure-Response Relationships in Epidemiologic Studies Using Standardized Mortality or Morbidity Ratios." Dose-Response 3, no. 4 (October 1, 2005): dose—response.0. http://dx.doi.org/10.2203/dose-response.003.04.003.

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In occupational epidemiology, exposure-response analyses play an important role in the evaluation of the etiologic relevance of chemical and physical exposures. The standardized mortality or morbidity ratio (SMR) has been commonly used in occupational cohort studies. Statistical approaches to evaluate exposure-response patterns using SMRs have mostly been limited to analyses in which the exposure under investigation is categorized. Here, a graphical method for evaluating exposure-response patterns is presented based on SMR estimates across moving exposure windows. This method is demonstrated using the results of two hypothetical cohort studies. The proposed approach may be useful for graphical exploration of exposure-response trends in situations where the number of observed cases is small.

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8

Sethi, Rajni A., Stephen C. Rush, Shian Liu, Suresh A. Sethi, Erik Parker, Bernadine Donahue, Ashwatha Narayana, Joshua Silverman, Douglas Kondziolka, and John G. Golfinos. "Dose-Response Relationships for Meningioma Radiosurgery." American Journal of Clinical Oncology 38, no. 6 (December 2015): 600–604. http://dx.doi.org/10.1097/coc.0000000000000008.

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9

Mandelbaum, B. R., A. T. C. Nasser, M. S. Watanabe, and B. S. Teurlings. "GYMNAST WRIST PAIN DOSE RESPONSE RELATIONSHIPS." Medicine & Science in Sports & Exercise 24, Supplement (May 1992): S46. http://dx.doi.org/10.1249/00005768-199205001-00276.

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10

ULM, K. "Nonparametric Analysis of Dose-Response Relationships." Annals of the New York Academy of Sciences 895, no. 1 UNCERTAINTY I (December 1999): 223–31. http://dx.doi.org/10.1111/j.1749-6632.1999.tb08088.x.

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11

Cullen, M. H. "Dose-response relationships in testicular cancer." European Journal of Cancer and Clinical Oncology 27, no. 7 (July 1991): 817–18. http://dx.doi.org/10.1016/0277-5379(91)90122-t.

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12

Heikinheimo, Oskari, and Raimo Kekkonen. "Dose-Response Relationships of RU 486." Annals of Medicine 25, no. 1 (January 1993): 71–76. http://dx.doi.org/10.3109/07853899309147861.

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13

NEUBERT, Diether, Gerd OCHERT, Thomas PLATZEK, Ibrahim CHAHOUD, Bernd FISCHER, and Reinhard MEISTER. "Dose-Response Relationships in Prenatal Toxicity." Congenital Anomalies 27, no. 3 (September 1987): 275–302. http://dx.doi.org/10.1111/j.1741-4520.1987.tb00711.x.

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14

Johnston, G. D. "Dose-response relationships with antihypertensive drugs." Pharmacology & Therapeutics 55, no. 1 (January 1992): 53–93. http://dx.doi.org/10.1016/0163-7258(92)90029-y.

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15

Rambiritch, Virendra, Poobalan Naidoo, and Neil Butkow. "Dose-Response Relationships of Sulfonylureas: Will Doubling the Dose Double the Response?" Southern Medical Journal 100, no. 11 (November 2007): 1132–36. http://dx.doi.org/10.1097/smj.0b013e318158420f.

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16

Roy, Nelson. "Optimal dose–response relationships in voice therapy." International Journal of Speech-Language Pathology 14, no. 5 (May 10, 2012): 419–23. http://dx.doi.org/10.3109/17549507.2012.686119.

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17

Zeise, L., R. Wilson, and E. A. Crouch. "Dose-response relationships for carcinogens: a review." Environmental Health Perspectives 73 (August 1987): 259–306. http://dx.doi.org/10.1289/ehp.8773259.

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18

Mavissakalian, M. R., and J. M. Perel. "IMIPRAMINE IN PANIC DISORDER: DOSE/RESPONSE RELATIONSHIPS." Clinical Neuropharmacology 15 (1992): 59B. http://dx.doi.org/10.1097/00002826-199202001-00112.

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19

Lundov, Michael D., Claus Zachariae, and Jeanne D. Johansen. "Methylisothiazolinone contact allergy and dose-response relationships." Contact Dermatitis 64, no. 6 (April 19, 2011): 330–36. http://dx.doi.org/10.1111/j.1600-0536.2011.01901.x.

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20

Schneider, A. B. "Dose-response relationships for radiation-induced hyperparathyroidism." Journal of Clinical Endocrinology & Metabolism 80, no. 1 (January 1, 1995): 254–57. http://dx.doi.org/10.1210/jc.80.1.254.

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21

Hamasaki, Toshimitsu, Tatsuya Isomura, Mitsumasa Baba, and Masashi Goto. "Statistical Approaches to Detecting Dose-Response Relationships." Drug Information Journal 34, no. 2 (April 2000): 579–90. http://dx.doi.org/10.1177/009286150003400226.

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22

Turner, Steven W., Cheng Wen, Ming Li, Tafline B. Fraser, and Judith A. Whitworth. "Adrenocorticotrophin dose–response relationships in the rat." Journal of Hypertension 16, no. 5 (May 1998): 593–600. http://dx.doi.org/10.1097/00004872-199816050-00006.

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23

EUN, H. C., and R. MARKS. "Dose—response relationships for topically applied antigens." British Journal of Dermatology 122, no. 4 (April 1990): 491–99. http://dx.doi.org/10.1111/j.1365-2133.1990.tb14726.x.

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24

Schneider, A. B., T. C. Gierlowski, E. Shore-Freedman, M. Stovall, E. Ron, and J. Lubin. "Dose-response relationships for radiation-induced hyperparathyroidism." Journal of Clinical Endocrinology & Metabolism 80, no. 1 (January 1995): 254–57. http://dx.doi.org/10.1210/jcem.80.1.7829622.

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25

Brammer, A. J. "Dose-response relationships for hand-transmitted vibration." Scandinavian Journal of Work, Environment & Health 12, no. 4 (August 1986): 284–88. http://dx.doi.org/10.5271/sjweh.2139.

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26

Randel, G. I., C. A. Shanks, S. J. Cooper, J. Zhao, R. J. Fragen, T. C. Krejcie, and M. J. Avram. "Thiopental Bolus Dose-Response Relationships in Man." Anesthesiology 89, Supplement (September 1998): 516A. http://dx.doi.org/10.1097/00000542-199809090-00035.

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27

Baayen, C., and P. Hougaard. "Confidence bounds for nonlinear dose-response relationships." Statistics in Medicine 34, no. 27 (June 25, 2015): 3546–62. http://dx.doi.org/10.1002/sim.6566.

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28

Kennedy, Sean W., and Donald C. Wigfield. "Dose-response relationships in hexachlorobenzene-induced porphyria." Biochemical Pharmacology 40, no. 6 (September 1990): 1381–88. http://dx.doi.org/10.1016/0006-2952(90)90407-c.

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29

Calabrese, Edward J., and Linda A. Baldwin. "A general classification of U-shaped dose-response relationships in toxicology and their mechanistic foundations." Human & Experimental Toxicology 17, no. 7 (July 1998): 353–64. http://dx.doi.org/10.1177/096032719801700701.

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The development of a comprehensive database of chemical hormetic responses (i.e., U-or inverted U-shaped dose-response relationships) using objective a priori study design, statistical and study replication criteria has recently been reported.1An assessment of this database reveals the existence of a wide range of hormetic dose-reponse relationships including those demonstrating a direct stimulation or an overcompensation response to a disruption of homeostasis. These two broad types of hormetic responses are affected by temporal factors and display unique patterns of dose-range stimulation, magnitude of stimulatory response and relationship of the maximum stimulatory response to the NOAEL. A general classification of U-shaped dose-response relationships is proposed to provide a more organized framework to evaluate the highly distinctive and diverse hormetic responses within the context of establishing underlying biological mechanisms and exploring risk assessment implications.

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30

Brooks, Antone L., and Lezlie Couch. "Doe Program—Developing a Scientific Basis for Responses to Low-Dose Exposures: Impact on Dose-Response Relationships." Dose-Response 5, no. 1 (January 2007): dose—response.0. http://dx.doi.org/10.2203/dose-response.06-001.brooks.

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31

Kimber, I., and D. Basketter. "Thresholds, dose-response relationships and dose metrics in allergic contact dermatitis." British Journal of Dermatology 159, no. 6 (December 2008): 1380–81. http://dx.doi.org/10.1111/j.1365-2133.2008.08868.x.

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32

Seefeldt, Steven S., Jens Erik Jensen, and E. Patrick Fuerst. "Log-Logistic Analysis of Herbicide Dose-Response Relationships." Weed Technology 9, no. 2 (June 1995): 218–27. http://dx.doi.org/10.1017/s0890037x00023253.

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Dose-response studies are an important tool in weed science. The use of such studies has become especially prevalent following the widespread development of herbicide resistant weeds. In the past, analyses of dose-response studies have utilized various types of transformations and equations which can be validated with several statistical techniques. Most dose-response analysis methods 1) do not accurately describe data at the extremes of doses and 2) do not provide a proper statistical test for the difference(s) between two or more dose-response curves. Consequently, results of dose-response studies are analyzed and reported in a great variety of ways, and comparison of results among various researchers is not possible. The objective of this paper is to review the principles involved in dose-response research and explain the log-logistic analysis of herbicide dose-response relationships. In this paper the log-logistic model is illustrated using a nonlinear computer analysis of experimental data. The log-logistic model is an appropriate method for analyzing most dose-response studies. This model has been used widely and successfully in weed science for many years in Europe. The log-logistic model possesses several clear advantages over other analysis methods and the authors suggest that it should be widely adopted as a standard herbicide dose-response analysis method.

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33

Coulson, J. M., and B. W. Hughes. "Dose-response relationships in aluminium toxicity in humans." Clinical Toxicology 60, no. 4 (February 18, 2022): 415–28. http://dx.doi.org/10.1080/15563650.2022.2029879.

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34

Sica, Domenic A. "Utilizing Dose-Response Relationships to Optimize Antihypertensive Efficacy." Southern Medical Journal 90, Supplement (December 1997): 5. http://dx.doi.org/10.1097/00007611-199712001-00005.

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35

Huy, Thomas, Kees De Schipper, Moira Chan-Yeung, and Susan M. Kennedy. "Grain Dust and Lung function: Dose-response Relationships." American Review of Respiratory Disease 144, no. 6 (December 1991): 1314–21. http://dx.doi.org/10.1164/ajrccm/144.6.1314.

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36

Day, Richard O., Diluk R. W. Kannangara, Sophie L. Stocker, Jane E. Carland, Kenneth M. Williams, and Garry G. Graham. "Allopurinol: insights from studies of dose–response relationships." Expert Opinion on Drug Metabolism & Toxicology 13, no. 4 (December 20, 2016): 449–62. http://dx.doi.org/10.1080/17425255.2017.1269745.

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37

SZETO, HAZEL H. "Maternal-Fetal Pharmacokinetics and Fetal Dose-Response Relationships." Annals of the New York Academy of Sciences 562, no. 1 Prenatal Abus (June 1989): 42–55. http://dx.doi.org/10.1111/j.1749-6632.1989.tb21006.x.

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38

Nieder, Carsten, Ursula Nestle, Karin Walter, Marcus Niewald, and Klaus Schnabel. "Dose–Response Relationships for Radiotherapy of Brain Metastases." American Journal of Clinical Oncology: Cancer Clinical Trials 23, no. 6 (December 2000): 584–88. http://dx.doi.org/10.1097/00000421-200012000-00011.

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39

T, Fletcher. "PFAS Dose Response Relationships and New Research Strategies." Environmental Epidemiology 3 (October 2019): 124. http://dx.doi.org/10.1097/01.ee9.0000607096.58335.bd.

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40

French, Jonathan L., and Paige L. Williams. "Characterizing Dose-Response Relationships in Multiple Cancer Bioassays." Risk Analysis 21, no. 1 (February 2001): 91–102. http://dx.doi.org/10.1111/0272-4332.211092.

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41

Anno, G. H., R. W. Young, R. M. Bloom, and J. R. Mercier. "DOSE RESPONSE RELATIONSHIPS FOR ACUTE IONIZING-RADIATION LETHALITY." Health Physics 84, no. 5 (May 2003): 565–75. http://dx.doi.org/10.1097/00004032-200305000-00001.

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42

Linden, Ariel, Paul R. Yarnold, and Brahmajee K. Nallamothu. "Using machine learning to model dose-response relationships." Journal of Evaluation in Clinical Practice 22, no. 6 (May 30, 2016): 860–67. http://dx.doi.org/10.1111/jep.12573.

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43

Lindblad, Ulf, and Arne Melander. "Sulphonylurea dose-response relationships: relation to clinical practice." Diabetes, Obesity and Metabolism 2, no. 1 (January 2000): 25–31. http://dx.doi.org/10.1046/j.1463-1326.2000.00046.x.

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44

Calabrese, Edward J., Edward J. Stanek, and Marc A. Nascarella. "Evidence for hormesis in mutagenicity dose–response relationships." Mutation Research/Genetic Toxicology and Environmental Mutagenesis 726, no. 2 (December 2011): 91–97. http://dx.doi.org/10.1016/j.mrgentox.2011.04.006.

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45

Leff, A. "Dose-response relationships in determining the safety:efficacy ratio." Respiratory Medicine 91 (November 1997): 34–37. http://dx.doi.org/10.1016/s0954-6111(97)90105-0.

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46

Bhasin, Shalender, Linda Woodhouse, Richard Casaburi, Atam B. Singh, Dimple Bhasin, Nancy Berman, Xianghong Chen, et al. "Testosterone dose-response relationships in healthy young men." American Journal of Physiology-Endocrinology and Metabolism 281, no. 6 (December 1, 2001): E1172—E1181. http://dx.doi.org/10.1152/ajpendo.2001.281.6.e1172.

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Testosterone increases muscle mass and strength and regulates other physiological processes, but we do not know whether testosterone effects are dose dependent and whether dose requirements for maintaining various androgen-dependent processes are similar. To determine the effects of graded doses of testosterone on body composition, muscle size, strength, power, sexual and cognitive functions, prostate-specific antigen (PSA), plasma lipids, hemoglobin, and insulin-like growth factor I (IGF-I) levels, 61 eugonadal men, 18–35 yr, were randomized to one of five groups to receive monthly injections of a long-acting gonadotropin-releasing hormone (GnRH) agonist, to suppress endogenous testosterone secretion, and weekly injections of 25, 50, 125, 300, or 600 mg of testosterone enanthate for 20 wk. Energy and protein intakes were standardized. The administration of the GnRH agonist plus graded doses of testosterone resulted in mean nadir testosterone concentrations of 253, 306, 542, 1,345, and 2,370 ng/dl at the 25-, 50-, 125-, 300-, and 600-mg doses, respectively. Fat-free mass increased dose dependently in men receiving 125, 300, or 600 mg of testosterone weekly (change +3.4, 5.2, and 7.9 kg, respectively). The changes in fat-free mass were highly dependent on testosterone dose ( P = 0.0001) and correlated with log testosterone concentrations ( r = 0.73, P = 0.0001). Changes in leg press strength, leg power, thigh and quadriceps muscle volumes, hemoglobin, and IGF-I were positively correlated with testosterone concentrations, whereas changes in fat mass and plasma high-density lipoprotein (HDL) cholesterol were negatively correlated. Sexual function, visual-spatial cognition and mood, and PSA levels did not change significantly at any dose. We conclude that changes in circulating testosterone concentrations, induced by GnRH agonist and testosterone administration, are associated with testosterone dose- and concentration-dependent changes in fat-free mass, muscle size, strength and power, fat mass, hemoglobin, HDL cholesterol, and IGF-I levels, in conformity with a single linear dose-response relationship. However, different androgen-dependent processes have different testosterone dose-response relationships.

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47

Rylander, Ragnar, Martin Björkman, Ulla Åhrlin, Eystein Arntzen, and Sigurd Solberg. "Dose-Response Relationships for Traffic Noise and Annoyance." Archives of Environmental Health: An International Journal 41, no. 1 (February 1986): 7–10. http://dx.doi.org/10.1080/00039896.1986.9935758.

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48

Whitworth, Craig, Craig Morris, Vernedra Scott, and Leonard P. Rybak. "Dose-response relationships for furosemide ototoxicity in rat." Hearing Research 71, no. 1-2 (December 1993): 202–7. http://dx.doi.org/10.1016/0378-5955(93)90035-y.

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49

Waud, D. R., and B. E. Waud. "Heuristic and practical graphing of dose-response relationships." Trends in Pharmacological Sciences 6 (January 1985): 26–30. http://dx.doi.org/10.1016/0165-6147(85)90012-4.

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50

Bárdossy, András, István Bogárdi, and Lucien Duckstein. "Fuzzy nonlinear regression analysis of dose-response relationships." European Journal of Operational Research 66, no. 1 (April 1993): 36–51. http://dx.doi.org/10.1016/0377-2217(93)90204-z.

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