Die Nukleosidischen Reverse Transkriptase Hemmer (NRTI) Zidovudin (AZT) und Stavudin (d4T) sind häufig eingesetzte Bestandteile der antiretroviralen Kombinationstherapie. Die Behandlung erstreckt sich oft über viele Jahre, sodass neben der antiviralen und immunologischen Effektivität besonders das Auftreten von Langzeitnebenwirkungen von Bedeutung ist. Im Rahmen dieser Arbeit wurden retrospektiv die Langzeit-Therapieverläufe von 213 Patienten, die zwischen 1990 und 2003 mit Zidovudin oder Stavudin behandelt wurden, verglichen. Die Kombinationsegime unterschieden sich nicht in ihrer antiretroviralen Wirksamkeit oder Einnahmedauer, jedoch in ihrem Nebenwirkungsprofil. So traten hämatologische Nebenwirkungen (Anämien, Leukopenien, Neutropenien) signifikant häufiger unter AZT auf. Die Gabe von Stavudin kann die hämatotoxische Wirkung von Zidovudin zum Teil kompensieren. Nach Therapieumstellung von AZT auf d4T kam es zu einem Anstieg der absoluten Leukozyten, der neutrophilen Granulozyten und des Hämoglobins. Sowohl in Zidovudin- als auch Stavudin-haltigen Regimen trat nach Beginn der antiretroviralen Therapie eine Makrozytose auf. Patienten mit Noncompliance zeigten eine anhaltende Normozytose bzw. eine Normalisierung des MCV, falls nach Beginn der ART eine Makrozytose bestand. Das MCV kann als Compliancemarker genutzt werden. Unter d4T-haltigen Regimen traten häufiger metabolische Nebenwirkungen wie Hypercholesterinämien, Hypertriglyceridämien und Hepatotoxizität auf, v.a. in Kombination mit Proteaseinhibitoren. Lipodystrophien wurden unter Proteasehemmer-haltigen und –freien Regimen beobachtet. Unter Stavudin traten Veränderungen der Körperfettverteilung signifikant häufiger auf als unter Zidovudin. / Zidovudine and stavudine, both NRTI, are frequently used drugs in antiretroviral therapies (ART). The ART will be given for many years, so long-term toxicities are an important limitating factor. In this study the antiretroviral therapies of 213 patients, who have been treated with zidovudine or stavudine between 1990 and 2003, were compared retrospectively. The regimens don’t differ from antiviral efficacy or time on ART but from adverse reactions. Hematologic complications (anemia, leucopenia, neutropenia) are common effects of zidovudine. Macrocytosis has been observed in zidovudine- and stavudine-containing regimens. Persons with noncompliance showed a normal mean corpuscular volume (MCV). It can be used to assess noncompliance. Under d4T-containing therapies metabolic complications like hypertriglyceridemia, hypercholesterolemia and hepatotoxicity occurred more often than under zidovudine, especially in combination with PI. Lipodystrophy has been observed in PI-containing and sparing regimens. It occurred more often under stavudine than zidovudine.

Background: Although the growth-factor G-CSF is widely used to prevent granulotoxic side effects of cytotoxic chemotherapies, its optimal use is still unknown since treatment outcome depends on many parameters such as dosing and timing of chemotherapies, pharmaceutical derivative of G-CSF used and individual risk factors. We showed in the past that a pharmacokinetic and dynamic model of G-CSF and human granulopoiesis can be used to predict the performance of yet untested G-CSF schedules. However, only a single chemotherapy was considered so far. In the present paper, we propose a comprehensive model of chemotherapy toxicity and combine it with our cell kinetic model of granulopoiesis. Major assumptions are: proportionality of cell numbers and cell loss, delayed action of chemotherapy, drug, drugdose and cell stage specific toxicities, no interaction of drugs and higher toxicity of drugs at the first time of application. Correspondingly, chemotherapies can be characterized by a set of toxicity parameters which can be estimated by fitting the predictions of our model to clinical time series data of patients under therapy. Data were either extracted from the literature or were received from cooperating clinical study groups. Results: Model assumptions proved to be feasible in explaining granulotoxicity of 10 different chemotherapeutic drugs or drug-combinations applied in 33 different schedules with and without G-CSF. Risk groups of granulotoxicity were traced back to differences in toxicity parameters. Conclusion: We established a comprehensive model of combined G-CSF and chemotherapy action in humans which allows us to predict and compare the outcome of alternative G-CSF schedules. We aim to apply the model in different clinical contexts to optimize and individualize G-CSF treatment.

Background: Although the growth-factor G-CSF is widely used to prevent granulotoxic side effects of cytotoxic chemotherapies, its optimal use is still unknown since treatment outcome depends on many parameters such as dosing and timing of chemotherapies, pharmaceutical derivative of G-CSF used and individual risk factors. We showed in the past that a pharmacokinetic and dynamic model of G-CSF and human granulopoiesis can be used to predict the performance of yet untested G-CSF schedules. However, only a single chemotherapy was considered so far. In the present paper, we propose a comprehensive model of chemotherapy toxicity and combine it with our cell kinetic model of granulopoiesis. Major assumptions are: proportionality of cell numbers and cell loss, delayed action of chemotherapy, drug, drugdose and cell stage specific toxicities, no interaction of drugs and higher toxicity of drugs at the first time of application. Correspondingly, chemotherapies can be characterized by a set of toxicity parameters which can be estimated by fitting the predictions of our model to clinical time series data of patients under therapy. Data were either extracted from the literature or were received from cooperating clinical study groups. Results: Model assumptions proved to be feasible in explaining granulotoxicity of 10 different chemotherapeutic drugs or drug-combinations applied in 33 different schedules with and without G-CSF. Risk groups of granulotoxicity were traced back to differences in toxicity parameters. Conclusion: We established a comprehensive model of combined G-CSF and chemotherapy action in humans which allows us to predict and compare the outcome of alternative G-CSF schedules. We aim to apply the model in different clinical contexts to optimize and individualize G-CSF treatment.