Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms.

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.

Estimating long-term health risks after breast cancer radiotherapy: merging evidence from low and high doses.

In breast cancer radiotherapy, substantial radiation exposure of organs other than the treated breast cannot be avoided, potentially inducing second primary cancer or heart disease. While distant organs and large parts of nearby ones receive doses in the mGy-Gy range, small parts of the heart, lung and bone marrow often receive doses as high as 50 Gy. Contemporary treatment planning allows for considerable flexibility in the distribution of this exposure. To optimise treatment with regards to long-term health risks, evidence-based risk estimates are required for the entire broad range of exposures. Here, we thus propose an approach that combines data from medical and epidemiological studies with different exposure conditions. Approximating cancer induction as a local process, we estimate organ cancer risks by integrating organ-specific dose-response relationships over the organ dose distributions. For highly exposed organ parts, specific high-dose risk models based on studies with medical exposure are applied. For organs or their parts receiving relatively low doses, established dose-response models based on radiation-epidemiological data are used. Joining the models in the intermediate dose range leads to a combined, in general non-linear, dose response supported by data over the whole relevant dose range. For heart diseases, a linear model consistent with high- and low-dose studies is presented. The resulting estimates of long-term health risks are largely compatible with rate ratios observed in randomised breast cancer radiotherapy trials. The risk models have been implemented in a software tool PASSOS that estimates long-term risks for individual breast cancer patients.

Analytical formulas representing track-structure simulations on DNA damage induced by protons and light ions at radiotherapy-relevant energies.

Track structure based simulations valuably complement experimental research on biological effects of ionizing radiation. They provide information at the highest level of detail on initial DNA damage induced by diverse types of radiation. Simulations with the biophysical Monte Carlo code PARTRAC have been used for testing working hypotheses on radiation action mechanisms, for benchmarking other damage codes and as input for modelling subsequent biological processes. To facilitate such applications and in particular to enable extending the simulations to mixed radiation field conditions, we present analytical formulas that capture PARTRAC simulation results on DNA single- and double-strand breaks and their clusters induced in cells irradiated by ions ranging from hydrogen to neon at energies from 0.5 GeV/u down to their stopping. These functions offer a means by which radiation transport codes at the macroscopic scale could easily be extended to predict biological effects, exploiting a large database of results from micro-/nanoscale simulations, without having to deal with the coupling of spatial scales and running full track-structure calculations.

ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence.

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.

BIOPHYSICAL SIMULATION TOOL PARTRAC: MODELLING PROTON BEAMS AT THERAPY-RELEVANT ENERGIES.

The biophysical simulation tool PARTRAC has been primarily developed to model radiation physics, chemistry and biology on nanometre to micrometre scales. However, the tool can be applied in simulating radiation effects in an event-by-event manner over macroscopic volumes as well. Benchmark simulations are reported showing that PARTRAC does reproduce the macroscopic Bragg peaks of proton beams, although the penetration depths are underestimated by a few per cent for high-energy beams. PARTRAC also quantifies the increase in DNA damage and its complexity along the beam penetration depth. Enhanced biological effectiveness is predicted in particular within distal Bragg peak parts of therapeutic proton beams.

Feasibility of reducing differences in estimated doses in nuclear medicine between a patient-specific and a reference phantom.

The feasibility of reducing the differences between patient-specific internal doses and doses estimated using reference phantoms was evaluated. Relatively simple adjustments to a polygon-surface ICRP adult male reference phantom were applied to fit selected individual dimensions using the software Rhinoceros®4.0. We tested this approach on two patient-specific phantoms: the biggest and the smallest phantoms from the Helmholtz Zentrum München library. These phantoms have unrelated anatomy and large differences in body-mass-index. Three models approximating each patient's anatomy were considered: the voxel and the polygon-surface ICRP adult male reference phantoms and the adjusted polygon-surface reference phantom. The Specific Absorbed Fractions (SAFs) for internal photon and electron sources were calculated with the Monte Carlo code EGSnrc. Employing the time-integrated activity coefficients of a radiopharmaceutical (S)-4-(3-18F-fluoropropyl)-l-glutamic acid and the calculated SAFs, organ absorbed-dose coefficients were computed following the formalism promulgated by the Committee on Medical Internal Radiation Dose. We compared the absorbed-dose coefficients between each patient-specific phantom and other models considered with emphasis on the cross-fire component. The corresponding differences for most organs were notably lower for the adjusted reference models compared to the case when reference models were employed. Overall, the proposed approach provided reliable dose estimates for both tested patient-specific models despite the pronounced differences in their anatomy. To capture the full range of inter-individual anatomic variability more patient-specific phantoms are required. The results of this test study suggest a feasibility of estimating patient-specific doses within a relative uncertainty of 25% or less using adjusted reference models, when only simple phantom scaling is applied.

Anthropomorphic dual-lattice voxel models for optimizing image quality and dose.

Using numerical simulations, the influence of various imaging parameters on the resulting image can be determined for various imaging technologies. To achieve this, visualization of fine tissue structures needed to evaluate the image quality with different radiation quality and dose is essential. The present work examines a method that employs simulations of the imaging process using Monte Carlo methods and a combination of a standard and higher resolution voxel models. A hybrid model, based on nonlinear uniform rational B-spline and polygon mesh surfaces, was constructed from an existing voxel model of a female patient of a resolution in the range of millimeters. The resolution of the hybrid model was [Formula: see text], i.e., substantially finer than that of the original model. Furthermore, a high resolution lung voxel model [[Formula: see text] voxel volume, slice thickness: [Formula: see text]] was developed from the specimen of a left lung lobe. This has been inserted into the hybrid model, substituting its left lung lobe and resulting in a dual-lattice geometry model. "Dual lattice" means, in this context, the combination of voxel models with different resolutions. Monte Carlo simulations of radiographic imaging were performed and the fine structure of the lung was easily recognizable.

An Apoptosis-Inducing Peptidic Heptad That Efficiently Clusters Death Receptor†5.

Multivalent ligands of death receptors hold particular promise as tumor cell-specific therapeutic agents because they induce an apoptotic cascade in cancerous cells. Herein, we present a modular approach to generate death receptor 5 (DR5) binding constructs comprising multiple copies of DR5 targeting peptide (DR5TP) covalently bound to biomolecular scaffolds of peptidic nature. This strategy allows for efficient oligomerization of synthetic DR5TP-derived peptides in different spatial orientations using a set of enzyme-promoted conjugations or recombinant production. Heptameric constructs based on a short (60-75 residues) scaffold of a C-terminal oligomerization domain of human C4b binding protein showed remarkable proapoptotic activity (EC50=3 nm) when DR5TP was ligated to its carboxy terminus. Our data support the notion that inter-ligand distance, relative spatial orientation and copy number of receptor-binding modules are key prerequisites for receptor activation and cell killing.

A generic approach to engineer antibody pH-switches using combinatorial histidine scanning libraries and yeast display.

There is growing interest in the fast and robust engineering of protein pH-sensitivity that aims to reduce binding at acidic pH, compared to neutral pH. Here, we describe a novel strategy for the incorporation of pH-sensitive antigen binding functions into antibody variable domains using combinatorial histidine scanning libraries and yeast surface display. The strategy allows simultaneous screening for both, high affinity binding at pH 7.4 and pH-sensitivity, and excludes conventional negative selection steps. As proof of concept, we applied this strategy to incorporate pH-dependent antigen binding into the complementary-determining regions of adalimumab. After 3 consecutive rounds of separate heavy and light chain library screening, pH-sensitive variants could be isolated. Heavy and light chain mutations were combined, resulting in 3 full-length antibody variants that revealed sharp, reversible pH-dependent binding profiles. Dissociation rate constants at pH 6.0 increased 230- to 780-fold, while high affinity binding at pH 7.4 in the sub-nanomolar range was retained. Furthermore, binding to huFcRn and thermal stability were not affected by histidine substitutions. Overall, this study emphasizes a generalizable strategy for engineering pH-switch functions potentially applicable to a variety of antibodies and further proteins-based therapeutics.

Evaluation of a computer-adaptive test for the assessment of depression (D-CAT) in clinical application.

In the past, a German Computerized Adaptive Test, based on Item Response Theory (IRT), was developed for purposes of assessing the construct depression [Computer-adaptive test for depression (D-CAT)]. This study aims at testing the feasibility and validity of the real computer-adaptive application.The D-CAT, supplied by a bank of 64 items, was administered on personal digital assistants (PDAs) to 423 consecutive patients suffering from psychosomatic and other medical conditions (78 with depression). Items were adaptively administered until a predetermined reliability (r > or = 0.90) was attained. For validation purposes, the Hospital Anxiety and Depression Scale (HADS), the Centre for Epidemiological Studies Depression (CES-D) scale, and the Beck Depression Inventory (BDI) were administered. Another sample of 114 patients was evaluated using standardized diagnostic interviews [Composite International Diagnostic Interview (CIDI)].The D-CAT was quickly completed (mean 74 seconds), well accepted by the patients and reliable after an average administration of only six items. In 95% of the cases, 10 items or less were needed for a reliable score estimate. Correlations between the D-CAT and the HADS, CES-D, and BDI ranged between r = 0.68 and r = 0.77. The D-CAT distinguished between diagnostic groups as well as established questionnaires do.The D-CAT proved an efficient, well accepted and reliable tool. Discriminative power was comparable to other depression measures, whereby the CAT is shorter and more precise. Item usage raises questions of balancing the item selection for content in the future.

Massage therapy reduces physical discomfort and improves mood disturbances in women with breast cancer.

BACKGROUND. A randomized controlled trial was conducted to investigate the efficacy of classical massage treatment in reducing breast cancer-related symptoms and in improving mood disturbances. METHODS. Women diagnosed with primary breast cancer were randomized into an intervention group and a control group. For a period of 5 weeks, the intervention group received bi-weekly 30-min classical massages in the back and head-neck areas. The control group received no additional treatment to their routine healthcare. To evaluate treatment efficacy, the following validated questionnaires were administrated at baseline (T1), at the end of the intervention (T2), and at a followup at 11 weeks (T3): the Short Form-8 Health Survey, the European Organization of Research and Treatment of Cancer quality of life questionnaire breast module (EORTC QLQ-BR23), the Giessen Complaints Inventory (GBB), and the Berlin Mood Questionnaire (BSF). RESULTS. Eighty-six eligible women (mean age: 59 years) were enrolled in the study. A significantly higher reduction of physical discomfort was found in the intervention group compared with the control group at T2 (p=0.001) and at T3 (p=0.038). A decrease in fatigue was also observed. Women in the intervention group reported significantly lower mood disturbances at T2 (p<0.01) but not at T3. The effect of treatment on mood disturbances was significantly higher if a patient was treated continuously by the same masseur. CONCLUSION. Classical massage seems to be an effective adjuvant treatment for reducing physical discomfort and fatigue, and improving mood disturbances in women with early stage breast cancer.

An evaluation of patient-reported outcomes found computerized adaptive testing was efficient in assessing stress perception.

OBJECTIVES: This study aimed to develop and evaluate a first computerized adaptive test (CAT) for the measurement of stress perception (Stress-CAT), in terms of the two dimensions: exposure to stress and stress reaction. STUDY DESIGN AND SETTING: Item response theory modeling was performed using a two-parameter model (Generalized Partial Credit Model). The evaluation of the Stress-CAT comprised a simulation study and real clinical application. A total of 1,092 psychosomatic patients (N1) were studied. Two hundred simulees (N2) were generated for a simulated response data set. Then the Stress-CAT was given to n=116 inpatients, (N3) together with established stress questionnaires as validity criteria. RESULTS: The final banks included n=38 stress exposure items and n=31 stress reaction items. In the first simulation study, CAT scores could be estimated with a high measurement precision (SE<0.32; rho>0.90) using 7.0+/-2.3 (M+/-SD) stress reaction items and 11.6+/-1.7 stress exposure items. The second simulation study reanalyzed real patients data (N1) and showed an average use of items of 5.6+/-2.1 for the dimension stress reaction and 10.0+/-4.9 for the dimension stress exposure. Convergent validity showed significantly high correlations. CONCLUSIONS: The Stress-CAT is short and precise, potentially lowering the response burden of patients in clinical decision making.

Functioning and validity of a Computerized Adaptive Test to measure anxiety (A-CAT).

BACKGROUND: The aim of this study was to evaluate the Computerized Adaptive Test to measure anxiety (A-CAT), a patient-reported outcome questionnaire that uses computerized adaptive testing to measure anxiety. METHODS: The A-CAT builds on an item bank of 50 items that has been built using conventional item analyses and item response theory analyses. The A-CAT was administered on Personal Digital Assistants to n=357 patients diagnosed and treated at the department of Psychosomatic Medicine and Psychotherapy, Charité Berlin, Germany. For validation purposes, two subgroups of patients (n=110 and 125) answered the A-CAT along with established anxiety and depression questionnaires. RESULTS: The A-CAT was fast to complete (on average in 2 min, 38 s) and a precise item response theory based CAT score (reliability>.9) could be estimated after 4-41 items. On average, the CAT displayed 6 items (SD=4.2). Convergent validity of the A-CAT was supported by correlations to existing tools (Hospital Anxiety and Depression Scale-A, Beck Anxiety Inventory, Berliner Stimmungs-Fragebogen A/D, and State Trait Anxiety Inventory: r=.56-.66); discriminant validity between diagnostic groups was higher for the A-CAT than for other anxiety measures. CONCLUSIONS: The German A-CAT is an efficient, reliable, and valid tool for assessing anxiety in patients suffering from anxiety disorders and other conditions with significant potential for initial assessment and long-term treatment monitoring. Future research directions are to explore content balancing of the item selection algorithm of the CAT, to norm the tool to a healthy sample, and to develop practical cutoff scores.

Evaluation of the Roche cobas s 201 system and cobas TaqScreen multiplex test for blood screening: a European multicenter study.

BACKGROUND: The Roche cobas TaqScreen test, an automated, multiplex nucleic acid test for blood screening for hepatitis B virus (HBV) DNA, hepatitis C virus (HCV) RNA, human immunodeficiency virus type 1 (HIV-1) groups M and O, and HIV-2 RNA, on the cobas s 201 platform, was evaluated by six European blood screening laboratories. STUDY DESIGN AND METHODS: The 95 percent limit of detection (LOD) of the cobas TaqScreen test for HBV, HCV, and HIV-1, using dilutions of the WHO International Standards, were evaluated. The clinical performance was determined by testing between 2000 to 6000 routine donor samples. Some laboratories evaluated the robustness, cross-contamination, and workflow. RESULTS: The mean 95 percent LOD (95% lower and upper confidence intervals) for HBV, HCV, and HIV-1 across all the laboratories were 3.8 (range, 3.0-5.2), 10.8 (range, 8.4-14.4), and 56.7 (range, 43.0-79.2) IU/mL, respectively. A total of 23,716 donors were tested in pools of 6. Fourteen initially reactive pools were detected, of which 6 contained a reactive donation, giving a positive predictive value of the pool results of 43 percent. One of the reactive donations was a HBV yield case (hepatitis B surface antigen-negative/anti-HBc-positive). Evaluation of the workflow for the system showed that an optimized batch loading in which a pipettor (Hamilton Microlab Star IVD) was utilized to half capacity was better than a full batch loading. CONCLUSION: The 95 percent LOD for the three viruses were comparable to those obtained by Roche. The test and platform were shown to be sensitive, specific, flexible, and robust.

A software tool for modification of human voxel models used for application in radiation protection.

This note describes a new software tool called 'VolumeChange' that was developed to modify the masses and location of organs of virtual human voxel models. A voxel model is a three-dimensional representation of the human body in the form of an array of identification numbers that are arranged in slices, rows and columns. Each entry in this array represents a voxel; organs are represented by those voxels having the same identification number. With this tool, two human voxel models were adjusted to fit the reference organ masses of a male and a female adult, as defined by the International Commission on Radiological Protection (ICRP). The alteration of an already existing voxel model is a complicated process, leading to many problems that have to be solved. To solve those intricacies in an easy way, a new software tool was developed and is presented here. If the organs are modified, no bit of tissue, i.e. voxel, may vanish nor should an extra one appear. That means that organs cannot be modified without considering the neighbouring tissue. Thus, the principle of organ modification is based on the reassignment of voxels from one organ/tissue to another; actually deleting and adding voxels is only possible at the external surface, i.e. skin. In the software tool described here, the modifications are done by semi-automatic routines but including human control. Because of the complexity of the matter, a skilled person has to validate that the applied changes to organs are anatomically reasonable. A graphical user interface was designed to fulfil the purpose of a comfortable working process, and an adequate graphical display of the modified voxel model was developed. Single organs, organ complexes and even whole limbs can be edited with respect to volume, shape and location.

Development and evaluation of a computer adaptive test for 'Anxiety' (Anxiety-CAT).

Within the framework of item response theory (IRT), we developed a German version of an item bank, as well as a software application that can be employed to measure anxiety by means of a computer adaptive test (CAT). A sample of n = 2348 psychiatric and psychosomatic patients answered a set of up to 13 standardized questionnaires. 81 items drawn from these questionnaires were considered pertinent to the anxiety construct. Various tests were conducted to ensure the suitability of these items for an IRT-based assessment. After these tests, 50 items remained in the item bank and were calibrated using the Generalized Partial Credit Model. Simulation studies conducted on an independent sample of n = 1528 respondents indicate that 6-8 items suffice to measure the latent trait with high precision (standard error

The clinical significance of adaptation to changing health: a meta-analysis of response shift.

AIMS: When individuals experience changes in their health states, they may alter their internal standards, values, or conceptualization of quality of life (QOL). Such 'response shifts' can affect or distort QOL outcome measurement, which is of particular concern when evaluating medical or psychosocial interventions. Although clinicians and researchers acknowledge the occurrence of response shifts, little is known about the magnitude and clinical significance of those effects. To fill this gap in knowledge about response shift phenomena, we performed a meta-analysis on published QOL articles on response shift. METHODS: Extensive literature searches and multiple contacts with researchers yielded a collection of 494 articles for potential reviewing. We retained only published longitudinal studies that measured response shift, resulting in 26, of which 19 reported the requisite data for computing an effect size (ES). We calculated and compared the ESs for each study with regard to potential moderator variables: the QOL domains measured, disease group investigated, sample size, and response shift method used. We rated studies for quality to allow ES weighting. RESULTS: When we examined ES absolute values, we found that ES magnitude was small, with the largest ESs detected for fatigue, followed by global QOL, physical role limitation, psychological well-being, and pain (mean absolute value(ES(weighted)) = 0.32, 0.30, 0.24, 0.12, and 0.08, respectively). ESs varied considerably in direction. Aggregating raw ES scores over all studies led to positive and negative values canceling each other out (mean directional ES(weighted) = 0.17, 0.02, -0.01, 0.06, and 0.02, respectively). We found little evidence of an effect for the moderator variables examined. CONCLUSIONS: A definitive conclusion on the clinical significance of response shift cannot currently be drawn from existing studies. For a number of reasons, ES estimates were primarily based on then-test results, a method that is not without criticism, such as its susceptibility to recall bias. We recommend a standardized approach for reporting results of future response shift research to advance the field and to facilitate interpretation and comparisons across studies.

[Standardized diagnosing: computer-assisted (CIDI) diagnoses compared to clinically-judged diagnoses in a psychosomatic setting]. / Standardisierte Diagnosefindung: Computergestützte (CIDI)--versus klinische Diagnosestellungen an einer psychosomatischen Stichprobe.

BACKGROUND: Within the past two decades, there has been an increasing trend towards the use of empirically-based, standardized instruments to diagnose mental disorders. The purpose of this study was to investigate the congruence between clinically-derived and standardized computerized diagnoses using the Composite International Diagnostic Interview (CIDI) in a psychosomatic setting. PATIENTS AND METHODS: N = 230 inpatients treated at the Department of Psychosomatic Medicine, Charité Berlin, were diagnosed for mental disorders by experienced clinicians and by the CIDI according to the diagnostic criteria of ICD-10 and DSM-IV. RESULTS: Congruence between computerized and clinically-derived diagnoses for all mental disorders was fair to poor (kappa = 0.0 - 0.33). The diagnostic congruence of somatoform (F45), anxiety (F40 - 41), depressive (F32 - 34), eating (F50) and dissociative disorders (F44) and disorders due to psychoactive substance use (F10 - 19) was fairly low (kappa = 0.19 - 0.33). Diagnostic congruence of diagnoses of reactions to severe stress (F43) and obsessive compulsive disorders (F42) was particularly poor (kappa = 0.0 - 0.01). CONCLUSION: Overall diagnostic congruence between computerized and clinical diagnostics was unsatisfactory. Thus, the validity of computer-assisted standardized interviews - like the CIDI - is questionable in a psychosomatic setting.

Development of a computer-adaptive test for depression (D-CAT).

Depression is one of the most prevalent mental health problems and measuring depressive symptoms becomes increasingly important in science as well as medical practice. Computer Adaptive Tests (CAT) based on the Item Response Theory (IRT) promise to enhance measurement precision and reduce respondent's burden. Our aim was to develop a CAT application to measure depressive symptoms. Three thousand two hundred seventy psychosomatic patients answered an overall of 11 mental health questionnaires at the University Clinic in Berlin. Three independent reviewers rated 144 items out of these questionnaires as indicative of depressive symptoms. All items underwent six empirical steps to analyze unidimensionality, local independence and item discrimination. Finally 64 items could be used to calculate item parameters applying a Generalized Partial Credit Model (GPCM). CAT scores were estimated using an 'expected a posteriori' algorithm (EAP). Two simulation experiments showed that for theta values within the range of 2SD around the mean (98% of the cases), the latent trait can be estimated out of approximately six items with a predefined standard error of [Symbol: see text] 0.32 (reliability rho [Symbol: see text] 0.90). The CAT-scores correlated high with scores of all depression items (r = 0.95), with the Beck Depression Inventory (r = 0.79) and with a CES-D 8 item short form (r = 0.76). We conclude that the Depression-CAT measures depressive symptoms with high precision and low respondent burden.

[Disturbed regulation of self-esteem in patients with overt versus covert self-destructive behaviour]. / Störungen der Selbstwertregulation bei Patienten mit offen versus heimlich selbstschädigendem Verhalten.

OBJECTIVES: According to psychoanalytic models self-harming patients are characterised by an unstable self-system and a disturbed regulation of self-esteem. This is presumed to be denied or dissociated to a greater degree by those who harm themselves secretly (factitious patients) as compared to those who show open self-harm. It is hypothesised and empirically tested that self-destructive patients have more profound disorders of narcissistic self-regulation than patients without self-destruction, and that this should be more evident in patients with overt self-destructive behaviour. METHODS: The sample consists of 354 psychosomatic patients, 32 of whom demonstrated self-destructive behaviour (18 exclusively overt and 6 exclusively covert types of behaviour, according to Willenberg et al.). The narcissism inventory was applied. RESULTS: Self-destructive patients showed higher levels on the "threatened self"-dimension than psychosomatic patients without self-harm. Overtly self-harming patients showed a higher degree of narcissistic self-regulation than covertly self-destructive patients. CONCLUSIONS: This supports theoretical assumptions of a disturbed regulation of self-esteem in self-destructive patients, especially in overtly self-harming patients.