ESMO / ASCO Recommendations for a Global Curriculum in Medical Oncology Edition 2016

The European Society for Medical Oncology (ESMO) and the American Society of Clinical Oncology (ASCO) are publishing a new edition of the ESMO/ASCO Global Curriculum (GC) thanks to contribution of 64 ESMO-appointed and 32 ASCO-appointed authors. First published in 2004 and updated in 2010, the GC edition 2016 answers to the need for updated recommendations for the training of physicians in medical oncology by defining the standard to be fulfilled to qualify as medical oncologists. At times of internationalisation of healthcare and increased mobility of patients and physicians, the GC aims to provide state-of-the-art cancer care to all patients wherever they live. Recent progress in the field of cancer research has indeed resulted in diagnostic and therapeutic innovations such as targeted therapies as a standard therapeutic approach or personalised cancer medicine apart from the revival of immunotherapy, requiring specialised training for medical oncology trainees. Thus, several new chapters on technical contents such as molecular pathology, translational research or molecular imaging and on conceptual attitudes towards human principles like genetic counselling or survivorship have been integrated in the GC. The GC edition 2016 consists of 12 sections with 17 subsections, 44 chapters and 35 subchapters, respectively. Besides renewal in its contents, the GC underwent a principal formal change taking into consideration modern didactic principles. It is presented in a template-based format that subcategorises the detailed outcome requirements into learning objectives, awareness, knowledge and skills. Consecutive steps will be those of harmonising and implementing teaching and assessment strategies

Best Definitions of Multimorbidity to Identify Patients With High Health Care Resource Utilization.

To compare different definitions of multimorbidity to identify patients with higher health care resource utilization. We used a multinational retrospective cohort including 147,806 medical inpatients discharged from 11 hospitals in 3 countries (United States, Switzerland, and Israel) between January 1, 2010, and December 31, 2011. We compared the area under the receiver operating characteristic curve (AUC) of 8 definitions of multimorbidity, based on International Classification of Diseases codes defining health conditions, the Deyo-Charlson Comorbidity Index, the Elixhauser-van Walraven Comorbidity Index, body systems, or Clinical Classification Software categories to predict 30-day hospital readmission and/or prolonged length of stay (longer than or equal to the country-specific upper quartile). We used a lower (yielding sensitivity ≥90%) and an upper (yielding specificity ≥60%) cutoff to create risk categories. Definitions had poor to fair discriminatory power in the derivation (AUC, 0.61-0.65) and validation cohorts (AUC, 0.64-0.71). The definitions with the highest AUC were number of (1) health conditions with involvement of 2 or more body systems, (2) body systems, (3) Clinical Classification Software categories, and (4) health conditions. At the upper cutoff, sensitivity and specificity were 65% to 79% and 50% to 53%, respectively, in the validation cohort; of the 147,806 patients, 5% to 12% (7474 to 18,008) were classified at low risk, 38% to 55% (54,484 to 81,540) at intermediate risk, and 32% to 50% (47,331 to 72,435) at high risk. Of the 8 definitions of multimorbidity, 4 had comparable discriminatory power to identify patients with higher health care resource utilization. Of these 4, the number of health conditions may represent the easiest definition to apply in clinical routine. The cutoff chosen, favoring sensitivity or specificity, should be determined depending on the aim of the definition

Patterns of multimorbidity associated with 30-day readmission: a multinational study.

Multimorbidity is associated with higher healthcare utilization; however, data exploring its association with readmission are scarce. We aimed to investigate which most important patterns of multimorbidity are associated with 30-day readmission. We used a multinational retrospective cohort of 126,828 medical inpatients with multimorbidity defined as ≥2 chronic diseases. The primary and secondary outcomes were 30-day potentially avoidable readmission (PAR) and 30-day all-cause readmission (ACR), respectively. Only chronic diseases were included in the analyses. We presented the OR for readmission according to the number of diseases or body systems involved, and the combinations of diseases categories with the highest OR for readmission. Multimorbidity severity, assessed as number of chronic diseases or body systems involved, was strongly associated with PAR, and to a lesser extend with ACR. The strength of association steadily and linearly increased with each additional disease or body system involved. Patients with four body systems involved or nine diseases already had a more than doubled odds for PAR (OR 2.35, 95%CI 2.15-2.57, and OR 2.25, 95%CI 2.05-2.48, respectively). The combinations of diseases categories that were most strongly associated with PAR and ACR were chronic kidney disease with liver disease or chronic ulcer of skin, and hematological malignancy with esophageal disorders or mood disorders, respectively. Readmission was associated with the number of chronic diseases or body systems involved and with specific combinations of diseases categories. The number of body systems involved may be a particularly interesting measure of the risk for readmission in multimorbid patients

Association of patterns of multimorbidity with length of stay: A multinational observational study.

The aim of this study was to identify the combinations of chronic comorbidities associated with length of stay (LOS) among multimorbid medical inpatients.Multinational retrospective cohort of 126,828 medical inpatients with multimorbidity, defined as ≥2 chronic diseases (data collection: 2010-2011). We categorized the chronic diseases into comorbidities using the Clinical Classification Software. We described the 20 combinations of comorbidities with the strongest association with prolonged LOS, defined as longer than or equal to country-specific LOS, and reported the difference in median LOS for those combinations. We also assessed the association between the number of diseases or body systems involved and prolonged LOS.The strongest association with prolonged LOS (odds ratio [OR] 7.25, 95% confidence interval [CI] 6.64-7.91, P < 0.001) and the highest difference in median LOS (13 days, 95% CI 12.8-13.2, P < 0.001) were found for the combination of diseases of white blood cells and hematological malignancy. Other comorbidities found in the 20 top combinations had ORs between 2.37 and 3.65 (all with P < 0.001) and a difference in median LOS of 2 to 5 days (all with P < 0.001), and included mostly neurological disorders and chronic ulcer of skin. Prolonged LOS was associated with the number of chronic diseases and particularly with the number of body systems involved (≥7 body systems: OR 21.50, 95% CI 19.94-23.18, P < 0.001).LOS was strongly associated with specific combinations of comorbidities and particularly with the number of body systems involved. Describing patterns of multimorbidity associated with LOS may help hospitals anticipate resource utilization and judiciously allocate services to shorten LOS

Patterns of multimorbidity in medical inpatients: a multinational retrospective cohort study.

Multimorbidity is frequent and represents a significant burden for patients and healthcare systems. However, there are limited data on the most common combinations of comorbidities in multimorbid patients. We aimed to describe and quantify the most common combinations of comorbidities in multimorbid medical inpatients. We used a large retrospective cohort of adults discharged from the medical department of 11 hospitals across 3 countries (USA, Switzerland, and Israel) between 2010 and 2011. Diseases were classified into acute versus chronic. Chronic diseases were grouped into clinically meaningful categories of comorbidities. We identified the most prevalent combinations of comorbidities and compared the observed and expected prevalence of the combinations. We assessed the distribution of acute and chronic diseases and the median number of body systems in relationship to the total number of diseases. Eighty-six percent (n = 126,828/147,806) of the patients were multimorbid (≥ 2 chronic diseases), with a median of five chronic diseases; 13% of the patients had ≥ 10 chronic diseases. Among the most frequent combinations of comorbidities, the most prevalent comorbidity was chronic heart disease. Other high prevalent comorbidities included mood disorders, arthropathy and arthritis, and esophageal disorders. The ratio of chronic versus acute diseases was approximately 2:1. Multimorbidity affected almost 90% of patients, with a median of five chronic diseases. Over 10% had ≥ 10 chronic diseases. This identification and quantification of frequent combinations of comorbidities among multimorbid medical inpatients may increase awareness of what should be taken into account when treating such patients, a growth in the need for special care considerations