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DRKS00003894.

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Conditional survival (CS) is defined as the probability of surviving further t years, given that a patient has already survived s years after the diagnosis of a chronic disease. It is the simplest form of a dynamic prediction in which other events in the course of the disease or biomarker values measured up to time s can be incorporated. CS has attracted attention in recent years either in an absolute or relative form where the latter is based on a comparison with an age-adjusted normal population being highly relevant from a public health perspective. In its absolute form, CS constitutes the quantity of major interest in a clinical context. Given a clinical cohort of patients with a particular type of cancer, absolute CS can be estimated by conditional Kaplan-Meier estimates in strata defined, for example, by age and disease stage or by a conditional version of the Cox and other regression models for timeto-event data. CS can be displayed as a function of the prediction time s in parametric as well as nonparametric fashion. We illustrate the use of absolute CS in a large clinical cohort of patients with multiple myeloma. For investigating CS, it is necessary to ensure almost complete long-term follow-up of the patients enrolled in the clinical cohort and to consider potential age-stage migration as well as changing treatment modalities over time. CS provides valuable and relevant information on how prognosis develops over time. It also serves as a starting point for identifying factors related to long-term survival.

To enhance the quality and safety in cancer treatment, and in acknowledgement that medical errors occur, we have established 2 error management systems: one monitors chemotherapy errors, the other records all severe adverse events occurring in chemotherapy-treated cancer patients (SAE CTx ) in in-and outpatient treatment. These error systems have been implemented by our departmental ''Clinical Service Center,'' a multidisciplinary team which controls all chemotherapy protocols and orders prior to the medication reaching the patient. We performed a prospective cohort study in consecutive cancer patients who received chemotherapies in our department between January 2005 and December 2006. Over this 2-year period, 2,337 patients were treated, with an equal distribution as in-and outpatients: 22,216 consecutive chemotherapy orders were analyzed, of which 83.5% were completely flawless, whereas we detected and corrected medical and administrative errors in 17.1%: in 3.8%, these errors involved the chemotherapy itself, in 4.5% the patient data and in 8.7% missing written informed consent forms. Chemotherapy errors were less frequent in outpatients than inpatients (3.3 vs. 4.5%, respectively). In outpatients, the rate of chemotherapy errors decreased from 4% in 2005 to 2.8% in 2006, but remained stable for inpatients (4.4% 2005 vs. 4.7% 2006). Among a total of 3,792 detected errors, only 3 reached the patient, resulting in an error rate in patients of 0.079%. Therefore, since we detected a substantial number of chemotherapy-related errors and intercepted 99.9%, we recommend our efficient surveillance system as an important safety check, thereby ensuring that chemotherapies are delivered errorfree to cancer patients.

Comorbidities have been demonstrated to affect progression-free survival (PFS) and overall survival (OS), although their impact in multiple myeloma (MM) patients is as yet unsettled. We (1) assessed various comorbidities, (2) compared established comorbidity indices (CIs; Charlson comorbidity index (CCI), hematopoietic cell transplantation-specific comorbidity index (HCT-CI)), Kaplan Feinstein (KF) and Satariano index (SI) and (3) developed a MM-CI (Freiburger comorbidity index, FCI) in 127 MM patients. Univariate analysis determined moderate or severe pulmonary disease (hazard ratio (HR): 3.5, P<0.0001), renal impairment (via estimated glomerular filtration rate (eGFR); HR: 3.4, P=0.0018), decreased Karnofsky Performance Status (KPS, HR: 2.7, P=0.0004) and age (HR: 2, P=0.0114) as most important variables for diminished OS. Through multivariate analysis, the eGFR ⩽30 ml/min/1.73m2, impaired lung function and KPS ⩽70% were significant for decreased OS, with HRs of 2.9, 2.8 and 2.2, respectively. Combination of these risk factors within the FCI identified significantly different median OS rates of 118, 53 and 25 months with 0, 1 and 2 or 3 risk factors, respectively, (P<0.005). In light of our study, comorbidities are critical prognostic determinants for diminished PFS and OS. Moreover, comorbidity scores are important treatment decision tools and will be valuable to implement into future analyses and clinical trials in MM.

Monoclonal gammopathy of undetermined significance is one of the most common pre-malignant disorders. IgG and IgA monoclonal gammopathy of undetermined significance are precursor conditions of multiple myeloma; lightchain monoclonal gammopathy of undetermined significance of light-chain multiple myeloma; and IgM monoclonal gammopathy of undetermined significance of Waldenström's macroglobulinemia and other lymphoproliferative disorders. Clonal burden, as determined by bone marrow plasma cell percentage or M-protein level, as well as biological characteristics, including heavy chain isotype and light chain production, are helpful in predicting risk of progression of monoclonal gammopathy of undetermined significance to symptomatic disease. Furthermore, alterations in the bone marrow microenvironment of monoclonal gammopathy of undetermined significance patients result in an increased risk of venous and arterial thrombosis, infections, osteoporosis, and bone fractures. In addition, the small clone may occasionally be responsible for severe organ damage through the production of a monoclonal protein that has autoantibody activity or deposits in tissues. These disorders are rare and often require therapy directed at eradication of the underlying plasma cell or lymphoplasmacytic clone. In this review, we provide an overview of the clinical relevance of monoclonal gammopathy of undetermined significance. We also give general recommendations of how to diagnose and manage patients with monoclonal gammopathy of undetermined significance. ABSTRACT © F e r r a t a S t o r t i F o u n d a t i o nClinical relevance of MGUS haematologica | 2014; 99(6) 985 Figure 1. Model for the mechanisms that contribute to the development and progression of MGUS. Obesity, exposure to pesticides, radiation exposure, and personal history of autoimmune diseases, inflammatory conditions and infections are associated with an increased risk of MGUS. In addition, there is a genetic predisposition to MGUS. (A) Primary immunoglobulin heavy chain (IgH) translocations with 5 recurrent chromosomal partners (4p16, 6p21, 11q13, 16q23, 20q11) and hyperdiploidy are early events and associated with the initiation of limited clonal plasma cell proliferation in non-IgM MGUS. Acquisition of secondary chromosomal abnormalities (such as deletions of (parts of) chromosomes or secondary chromosomal translocations) and mutations involving individual genes results in the stepwise progression from MGUS to newly diagnosed symptomatic MM, and finally aggressive forms of MM such as sPCL or extramedullary MM. During this process there is a progressive replacement of normal/polyclonal plasma cells (orange) by clonal plasma cells (blue). Progression of the plasma cell disorder is also accompanied by altered interactions of the tumor cells with various components of their microenvironment such as osteoclasts, endothelial cells, and cells of the immune system. Recent evidence suggests the presence of intraclonal heterogeneity in MGUS, adding a further level of genetic compl...

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