LIVIVO - Search results -

Search results

Result 1 - 10 of total 177

Search options

Article ; Online: A composite semiparametric homogeneity test for the distributions of multigroup interval-bounded longitudinal data.

Wang, Zhanfeng / Li, Wenmei / Ding, Hao / Tu, Dongsheng

2023 , Page(s) 1–12

Abstract: Motivated by comparing the distribution of longitudinal quality of life (QoL) data among different treatment groups from a cancer clinical trial, we propose a semiparametric test statistic for the homogeneity of the distributions of multigroup ... ...

Abstract	Motivated by comparing the distribution of longitudinal quality of life (QoL) data among different treatment groups from a cancer clinical trial, we propose a semiparametric test statistic for the homogeneity of the distributions of multigroup longitudinal measurements, which are bounded in a closed interval with excess observations taking the boundary values. Our procedure is based on a three-component mixed density ratio model and a composite empirical likelihood for the longitudinal data taking values inside the interval. A nonparametric bootstrap method is applied to calculate the p-value of the proposed test. Simulation studies are conducted to evaluate the proposed procedure, which show that the proposed test is effective in controlling type I errors and more powerful than the procedure which ignores the values on the boundaries. It is also robust to the model mispecification than the parametric test. The proposed procedure is also applied to compare the distributions of the scores of Physical Function subscale and Global Heath Status between the patients randomized to two treatment groups in a cancer clinical trial.
Language	English
Publishing date	2023-11-15
Publishing country	England
Document type	Journal Article
ZDB-ID	1131763-2
ISSN	1520-5711 ; 1054-3406
ISSN (online)	1520-5711
ISSN	1054-3406
DOI	10.1080/10543406.2023.2275769
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 3511: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: A threshold longitudinal Tobit quantile regression model for identification of treatment-sensitive subgroups based on interval-bounded longitudinal measurements and a continuous covariate.

Wang, Zhanfeng / Li, Tao / Xiao, Liqun / Tu, Dongsheng

Statistics in medicine

2023 Volume 42, Issue 25, Page(s) 4618–4631

Abstract: Identification of a subgroup of patients who may be sensitive to a specific treatment is an important problem in precision medicine. This article considers the case where the treatment effect is assessed by longitudinal measurements, such as quality of ... ...

Abstract	Identification of a subgroup of patients who may be sensitive to a specific treatment is an important problem in precision medicine. This article considers the case where the treatment effect is assessed by longitudinal measurements, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. Recently, a linear mixed threshold regression model has been proposed but it assumes the longitudinal measurements are normally distributed. In many applications, longitudinal measurements, such as quality of life data obtained from answers to questions on a Likert scale, may be restricted in a fixed interval because of the floor and ceiling effects and, therefore, may be skewed. In this article, a threshold longitudinal Tobit quantile regression model is proposed and a computational approach based on alternating direction method of multipliers algorithm is developed for the estimation of parameters in the model. In addition, a random weighting method is employed to estimate the variances of the parameter estimators. The proposed procedures are evaluated through simulation studies and applications to the data from clinical trials.
Language	English
Publishing date	2023-08-20
Publishing country	England
Document type	Journal Article
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.9879
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 1756: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article: Innovations in the Management of Musculoskeletal Pain With Alpha-Lipoic Acid (IMPALA Trial): Study protocol for a Double-Blind, Randomized, Placebo-Controlled Crossover Trial of Alpha-Lipoic Acid for the Treatment of Fibromyalgia Pain

Gilron, Ian / Tu, Dongsheng / Holden, Ronald / Towheed, Tanveer / Ziegler, Dan / Wang, Louie / Milev, Roumen / Gray, Christopher

JMIR Research Protocols, 6(3):e41

2017

Abstract: BACKGROUND: Fibromyalgia is a common disorder characterized by chronic widespread pain, sleep disturbance, fatigue, depression, and cognitive dysfunction, resulting in substantial disability. As current analgesics provide incomplete relief and disabling ... ...

Institution	Deutsches Diabetes-Zentrum
Abstract	BACKGROUND: Fibromyalgia is a common disorder characterized by chronic widespread pain, sleep disturbance, fatigue, depression, and cognitive dysfunction, resulting in substantial disability. As current analgesics provide incomplete relief and disabling side effects that aggravate fatigue and cognitive dysfunction, there is a need for new pain treatments with better efficacy and tolerability. Alpha-lipoic acid (ALA) is an antioxidant proven effective in painful diabetic neuropathy with minimal side effects. OBJECTIVE: We hypothesize that this agent will provide benefits in fibromyalgia because of several similarities with neuropathic pain and also because it does not cause sedation, fatigue, or mental-slowing. To test this, we have designed a clinical trial that will assess pain, side effects, and other outcomes in participants with fibromyalgia. METHODS: Using a crossover design, 24 adults with fibromyalgia will be randomly allocated to 1 of the 2 sequences of ALA and placebo. Participants will take capsules containing ALA or placebo for 4 weeks followed by a 1-week washout followed by a second 4-week treatment and 1-week washout period. ALA (or matching placebo) capsules will be titrated to 1800 mg/day over each 4-week period. The primary outcome will be mean daily pain intensity (0-10) during week 4 of each period. Secondary outcomes, assessed during week 4 of each period, will include global improvement, adverse events, mood, and quality of life. RESULTS: This trial was registered in the International Standard Randomized Controlled Trial registry March 15, 2016 (Number ISRCTN58259979), and it attained ethics approval on December 3, 2016 (Queen’s University Health Sciences & Affiliated Teaching Hospitals Research Ethics Board protocol number ANAE-287-15). The recruitment started in February 2017. CONCLUSIONS: This trial will provide evidence for the efficacy of ALA in fibromyalgia.
Keywords	antioxidants ; alpha-lipoic acid ; fibromyalgia ; pain
Language	English
Document type	Article
Database	Repository for Life Sciences

Full text online

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Unified estimation for Cox regression model with nonmonotone missing at random covariates.

Thiessen, David Luke / Zhao, Yang / Tu, Dongsheng

Statistics in medicine

2022 Volume 41, Issue 24, Page(s) 4781–4790

Abstract: This article investigates a unified estimator for Cox regression model (Cox, 1972) when covariate data are missing at random (Rubin, 1976). It extends the idea of using parametric working models (Zhao and Liu, 2021) to extract the partial information ... ...

Abstract	This article investigates a unified estimator for Cox regression model (Cox, 1972) when covariate data are missing at random (Rubin, 1976). It extends the idea of using parametric working models (Zhao and Liu, 2021) to extract the partial information contained in the incomplete observations. The working models are flexible and convenient to deal with nonmonotone missing data patterns. It can also incorporate auxiliary variables into the analysis to reduce estimation bias and improve efficiency. The unified estimator is consistent and more efficient than the (weighted) complete case estimator. Similar to multiple imputation (MI) method (Rubin, 1987 and 1996), the proposed method is also based on standard (weighted) complete data analysis and can be easily implemented in standard software. Simulation studies comparing the unified estimator with the substantive model compatible modification of the fully conditional specification MI (SMC-FCS) estimator (Bartlett et al., 2015) in various settings indicate that the unified estimator is consistent and as efficient as SMC-FCS estimator. Data from a clinical trial in patients with early breast cancer are analyzed for illustration.
MeSH term(s)	Bias ; Computer Simulation ; Humans ; Models, Statistical ; Proportional Hazards Models ; Research Design
Language	English
Publishing date	2022-07-04
Publishing country	England
Document type	Journal Article
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.9512
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 1756: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: A bootstrap semiparametric homogeneity test for the distributions of multigroup proportional data, with applications to analysis of quality of life outcomes in clinical trials.

Wang, Chunlin / Tu, Dongsheng

Statistics in medicine

2020 Volume 39, Issue 12, Page(s) 1715–1731

Abstract: This article is concerned about the test for the difference in the distributions of multigroup proportional data, which is motivated by the problem of comparing the distributions of quality of life (QoL) outcomes among different treatment groups in ... ...

Abstract	This article is concerned about the test for the difference in the distributions of multigroup proportional data, which is motivated by the problem of comparing the distributions of quality of life (QoL) outcomes among different treatment groups in clinical trials. The proportional data, such as QoL outcomes assessed by answers to questions on a questionnaire, are bounded in a closed interval such as [0,1] with continuous observations in (0,1) and, in addition, excess observations taking the boundary values 0 and/or 1. Common statistical procedures used in practice, such as t- and rank-based tests, may not be very powerful since they ignore the specific feature of the proportional data. In this article, we propose a three-component mixture model for the proportional data and a density ratio model for the distributions of continuous observations in (0,1). A semiparametric test statistic for the homogeneity of distributions of multigroup proportional data is derived based on the empirical likelihood ratio principle and shown to be asymptotically distributed as a chi-squared random variable under null hypothesis. A nonparametric bootstrap procedure is proposed to further improve the performance of the semiparametric test. Simulation studies are performed to evaluate the empirical type I error and power of the proposed test procedure and compare it with likelihood ratio tests (LRTs) under parametric distribution assumptions, rank-based Kruskal-Wallis test, and Wald-type test. The proposed test procedure is also applied to the analysis of QoL outcomes from a clinical trial on colorectal cancer that motivated our study.
MeSH term(s)	Computer Simulation ; Humans ; Likelihood Functions ; Quality of Life
Language	English
Publishing date	2020-02-25
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.8507
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 1756: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Multiply robust subgroup analysis based on a single-index threshold linear marginal model for longitudinal data with dropouts.

Wei, Kecheng / Zhu, Huichen / Qin, Guoyou / Zhu, Zhongyi / Tu, Dongsheng

Statistics in medicine

2022 Volume 41, Issue 15, Page(s) 2822–2839

Abstract: Identifying subpopulations that may be sensitive to the specific treatment is an important step toward precision medicine. On the other hand, longitudinal data with dropouts is common in medical research, and subgroup analysis for this data type is still ...

Abstract	Identifying subpopulations that may be sensitive to the specific treatment is an important step toward precision medicine. On the other hand, longitudinal data with dropouts is common in medical research, and subgroup analysis for this data type is still limited. In this paper, we consider a single-index threshold linear marginal model, which can be used simultaneously to identify subgroups with differential treatment effects based on linear combination of the selected biomarkers, estimate the treatment effects in different subgroups based on regression coefficients, and test the significance of the difference in treatment effects based on treatment-subgroup interaction. The regression parameters are estimated by solving a penalized smoothed generalized estimating equation and the selection bias caused by missingness is corrected by a multiply robust weighting matrix, which allows multiple missingness models to be taken account into estimation. The proposed estimator remains consistent when any model for missingness is correctly specified. Under regularity conditions, the asymptotic normality of the estimator is established. Simulation studies confirm the desirable finite-sample performance of the proposed method. As an application, we analyze the data from a clinical trial on pancreatic cancer.
MeSH term(s)	Computer Simulation ; Humans ; Linear Models ; Models, Statistical ; Research Design ; Selection Bias
Language	English
Publishing date	2022-03-28
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.9386
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 1756: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Estimation of the binomial probabilities in a two-stage phase II clinical trial with two co-primary endpoints.

Sun, Yiming / Zhang, Xinyi / Tan, Xianming / Tu, Dongsheng

Contemporary clinical trials

2021 Volume 105, Page(s) 106390

Abstract: In cancer research, two-stage designs are usually used to assess the effect of a new agent in phase II clinical trials. Optimal two-stage designs with two co-primary endpoints have been proposed to assess the effects of new cancer treatments, such as ... ...

Abstract	In cancer research, two-stage designs are usually used to assess the effect of a new agent in phase II clinical trials. Optimal two-stage designs with two co-primary endpoints have been proposed to assess the effects of new cancer treatments, such as cytostatic or molecularly targeted agents (MTAs), based on both response rate and early progression rate. Accurate estimation of response and early progression rates based on the data from the phase II trials conducted according to the optimal two-stage designs would be very useful for further testing of the agents in phase II trials. In this paper, we derive some estimation procedures, which include both standard and bias-corrected maximum likelihood estimates (MLE) and uniformly minimum variance unbiased estimate (UMVUE), for two binomial probabilities which are used to define the hypotheses for two co-primary endpoints tested in a two-stage phase II clinical trial. Simulation studies were performed to evaluate the performance of these procedures. These procedures are also applied to analyze the data from a phase II trial conducted by the Canadian Cancer Trials Group.
MeSH term(s)	Bias ; Canada ; Computer Simulation ; Humans ; Likelihood Functions ; Neoplasms/drug therapy ; Research Design
Language	English
Publishing date	2021-04-02
Publishing country	United States
Document type	Clinical Trial, Phase II ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2182176-8
ISSN	1559-2030 ; 1551-7144
ISSN (online)	1559-2030
ISSN	1551-7144
DOI	10.1016/j.cct.2021.106390
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 1581: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Two-stage multivariate Mendelian randomization on multiple outcomes with mixed distributions.

Deng, Yangqing / Tu, Dongsheng / O'Callaghan, Chris J / Liu, Geoffrey / Xu, Wei

Statistical methods in medical research

2023 Volume 32, Issue 8, Page(s) 1543–1558

Abstract: In clinical research, it is important to study whether certain clinical factors or exposures have causal effects on clinical and patient-reported outcomes such as toxicities, quality of life, and self-reported symptoms, which can help improve patient ... ...

Abstract	In clinical research, it is important to study whether certain clinical factors or exposures have causal effects on clinical and patient-reported outcomes such as toxicities, quality of life, and self-reported symptoms, which can help improve patient care. Usually, such outcomes are recorded as multiple variables with different distributions. Mendelian randomization (MR) is a commonly used technique for causal inference with the help of genetic instrumental variables to deal with observed and unobserved confounders. Nevertheless, the current methodology of MR for multiple outcomes only focuses on one outcome at a time, meaning that it does not consider the correlation structure of multiple outcomes, which may lead to a loss of statistical power. In situations with multiple outcomes of interest, especially when there are mixed correlated outcomes with different distributions, it is much more desirable to jointly analyze them with a multivariate approach. Some multivariate methods have been proposed to model mixed outcomes; however, they do not incorporate instrumental variables and cannot handle unmeasured confounders. To overcome the above challenges, we propose a two-stage multivariate Mendelian randomization method (MRMO) that can perform multivariate analysis of mixed outcomes using genetic instrumental variables. We demonstrate that our proposed MRMO algorithm can gain power over the existing univariate MR method through simulation studies and a clinical application on a randomized Phase III clinical trial study on colorectal cancer patients.
MeSH term(s)	Humans ; Genetic Variation ; Mendelian Randomization Analysis/methods ; Quality of Life ; Causality ; Computer Simulation
Language	English
Publishing date	2023-06-20
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1136948-6
ISSN	1477-0334 ; 0962-2802
ISSN (online)	1477-0334
ISSN	0962-2802
DOI	10.1177/09622802231181220
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 3564: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Combination analgesic development for enhanced clinical efficacy (the CADENCE trial): a double-blind, controlled trial of an alpha-lipoic acid-pregabalin combination for fibromyalgia pain.

Gilron, Ian / Robb, Sylvia / Tu, Dongsheng / Holden, Ronald R / Milev, Roumen / Towheed, Tanveer

Pain

2023 Volume 164, Issue 8, Page(s) 1783–1792

Abstract: Abstract: Drug therapy for fibromyalgia is limited by incomplete efficacy and dose-limiting adverse effects (AEs). Combining agents with complementary analgesic mechanisms-and differing AE profiles-could provide added benefits. We assessed an alpha- ... ...

Abstract	Abstract: Drug therapy for fibromyalgia is limited by incomplete efficacy and dose-limiting adverse effects (AEs). Combining agents with complementary analgesic mechanisms-and differing AE profiles-could provide added benefits. We assessed an alpha-lipoic acid (ALA)-pregabalin combination with a randomized, double-blind, 3-period crossover design. Participants received maximally tolerated doses of ALA, pregabalin, and ALA-pregabalin combination for 6 weeks. The primary outcome was daily pain (0-10); secondary outcomes included Fibromyalgia Impact Questionnaire, SF-36 survey, Medical Outcomes Study Sleep Scale, Beck Depression Inventory (BDI-II), adverse events, and other measures. The primary outcome of daily pain (0-10) during ALA (4.9), pregabalin (4.6), and combination (4.5) was not significantly different ( P = 0.54). There were no significant differences between combination and each monotherapy for any secondary outcomes, although combination and pregabalin were both superior to ALA for measures of mood and sleep. Alpha-lipoic acid and pregabalin maximal tolerated doses were similar during combination and monotherapy, and AEs were not frequent with combination therapy. These results do not support any additive benefit of combining ALA with pregabalin for fibromyalgia. The observation of similarly reached maximal tolerated drug doses of these 2 agents (which have differing side-effect profiles) during combination and monotherapy-without increased side effects-provides support for future development of potentially more beneficial combinations with complementary mechanisms and nonoverlapping side effects.
MeSH term(s)	Humans ; Pregabalin/therapeutic use ; Fibromyalgia/drug therapy ; Fibromyalgia/complications ; Thioctic Acid/therapeutic use ; gamma-Aminobutyric Acid/therapeutic use ; Analgesics ; Pain/drug therapy ; Treatment Outcome ; Double-Blind Method
Chemical Substances	Pregabalin (55JG375S6M) ; Thioctic Acid (73Y7P0K73Y) ; gamma-Aminobutyric Acid (56-12-2) ; Analgesics
Language	English
Publishing date	2023-03-06
Publishing country	United States
Document type	Randomized Controlled Trial ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	193153-2
ISSN	1872-6623 ; 0304-3959
ISSN (online)	1872-6623
ISSN	0304-3959
DOI	10.1097/j.pain.0000000000002875
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 1158: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: A threshold linear mixed model for identification of treatment-sensitive subsets in a clinical trial based on longitudinal outcomes and a continuous covariate.

Ge, Xinyi / Peng, Yingwei / Tu, Dongsheng

Statistical methods in medical research

2020 Volume 29, Issue 10, Page(s) 2919–2931

Abstract: Identification of a subset of patients who may be sensitive to a specific treatment is an important problem in clinical trials. In this paper, we consider the case where the treatment effect is measured by longitudinal outcomes, such as quality of life ... ...

Abstract	Identification of a subset of patients who may be sensitive to a specific treatment is an important problem in clinical trials. In this paper, we consider the case where the treatment effect is measured by longitudinal outcomes, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. A threshold linear mixed model is introduced, and a smoothing maximum likelihood method is proposed to obtain the estimation of the parameters in the model. Broyden-Fletcher-Goldfarb-Shanno algorithm is employed to maximize the proposed smoothing likelihood function. The proposed procedure is evaluated through simulation studies and application to the analysis of data from a randomized clinical trial on patients with advanced colorectal cancer.
MeSH term(s)	Algorithms ; Computer Simulation ; Humans ; Likelihood Functions ; Linear Models ; Quality of Life
Language	English
Publishing date	2020-03-20
Publishing country	England
Document type	Journal Article ; Randomized Controlled Trial ; Research Support, Non-U.S. Gov't
ZDB-ID	1136948-6
ISSN	1477-0334 ; 0962-2802
ISSN (online)	1477-0334
ISSN	0962-2802
DOI	10.1177/0962280220912772
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 3564: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

To top

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito