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The disease management of long-term breast cancer survivors (BCS) is hampered by the scarce knowledge of multimorbidity patterns. The aim of our study was to identify multimorbidity clusters among long-term BCS and assess their impact on mortality and health services use. We conducted a retrospective study using electronic health records of 6512 BCS from Spain surviving at least 5 years. Hierarchical cluster analysis was used to identify groups of similar patients based on their chronic diagnoses, which were assessed using the Clinical Classifications Software. As a result, multimorbidity clusters were obtained, clinically defined and named according to the comorbidities with higher observed/expected prevalence ratios. Multivariable Cox and negative binomial regression models were fitted to estimate overall mortality risk and probability of contacting health services according to the clusters identified. 83.7% of BCS presented multimorbidity, essential hypertension (34.5%) and obesity and other metabolic disorders (27.4%) being the most prevalent chronic diseases at the beginning of follow-up. Five multimorbidity clusters were identified: C1-unspecific (29.9%), C2-metabolic and neurodegenerative (28.3%), C3-anxiety and fractures (9.7%), C4-musculoskeletal and cardiovascular (9.6%) and C5-thyroid disorders (5.3%). All clusters except C5-thyroid disorders were associated with higher mortality compared to BCS without comorbidities. The risk of mortality in C4 was increased by 64% (adjusted hazard ratio 1.64, 95% confidence interval 1.52-2.07). Stratified analysis showed an increased risk of death among BCS with 5 to 10 years of survival in all clusters. These results help to identify subgroups of long-term BCS with specific needs and mortality risks and to guide BCS clinical practice regarding multimorbidity.

REDISSEC-CARESS/CCR group., [Introduction] Few studies have been conducted to establish the relationship between colorectal cancer screening programmes and survival adjusting by stage and, to determine whether there are differences, at a biological level, between the tumours of asymptomatic and symptomatic patients. Accordingly, the aim of this study is to evaluate clinical, biological and survival differences between symptomatic colorectal tumours and those detected by screening., [Study method] A prospective cohort study was performed of patients subjected to surgical intervention during the period 2010–2012, at different hospitals in Spain. In every case, clinical, pathological, biological and survival-related variables were obtained., [Results] A total of 2634 patients from the CARESS-CCR cohort were analysed; of these, 220 were diagnosed through screening. The asymptomatic patients were younger, had a higher Body Mass Index (BMI), a lower degree of perineural invasion and a less advanced T stage and nodular stage, and the tumour was frequently located on the right side of the colon. All of these differences were statistically significant. The serum tumour marker carbohydrate antigen 19.9 (CA 19.9) was found more frequently in the symptomatic patients (p, [Conclusions] The detection method employed influenced the survival of patients with colorectal cancer and there were no significant biological differences between the study groups., This research was partially supported by grants from REDISSEC (RD12/0001/0010 and RD16/0001/0006), Instituto de Salud Carlos III (PI 09/00910, PI 13/00013, PI 18/01181) and the European Regional Development Fund.

Aims: To investigate the prevalence of suicidal thoughts and behaviours (STB; i.e. suicidal ideation, plans or attempts) in the Spanish adult general population during the first wave of the Spain coronavirus disease 2019 (COVID-19) pandemic (March-July, 2020), and to investigate the individual- and population-level impact of relevant distal and proximal STB risk factor domains. Methods: Cross-sectional study design using data from the baseline assessment of an observational cohort study (MIND/COVID project). A nationally representative sample of 3500 non-institutionalised Spanish adults (51.5% female; mean age = 49.6 [s.d. = 17.0]) was taken using dual-frame random digit dialing, stratified for age, sex and geographical area. Professional interviewers carried out computer-assisted telephone interviews (1-30 June 2020). Thirty-day STB was assessed using modified items from the Columbia Suicide Severity Rating Scale. Distal (i.e. pre-pandemic) risk factors included sociodemographic variables, number of physical health conditions and pre-pandemic lifetime mental disorders; proximal (i.e. pandemic) risk factors included current mental disorders and a range of adverse events-experiences related to the pandemic. Logistic regression was used to investigate individual-level associations (odds ratios [OR]) and population-level associations (population attributable risk proportions [PARP]) between risk factors and 30-day STB. All data were weighted using post-stratification survey weights. Results: Estimated prevalence of 30-day STB was 4.5% (1.8% active suicidal ideation; n = 5 [0.1%] suicide attempts). STB was 9.7% among the 34.3% of respondents with pre-pandemic lifetime mental disorders, and 1.8% among the 65.7% without any pre-pandemic lifetime mental disorder. Factors significantly associated with STB were pre-pandemic lifetime mental disorders (total PARP = 49.1%) and current mental disorders (total PARP = 58.4%), i.e. major depressive disorder (OR = 6.0; PARP = 39.2%), generalised anxiety disorder (OR = 5.6; PARP = 36.3%), post-traumatic stress disorder (OR = 4.6; PARP = 26.6%), panic attacks (OR = 6.7; PARP = 36.6%) and alcohol/substance use disorder (OR = 3.3; PARP = 5.9%). Pandemic-related adverse events-experiences associated with STB were lack of social support, interpersonal stress, stress about personal health and about the health of loved ones (PARPs 32.7-42.6%%), and having loved ones infected with COVID-19 (OR = 1.7; PARP = 18.8%). Up to 74.1% of STB is potentially attributable to the joint effects of mental disorders and adverse events-experiences related to the pandemic. Conclusions: STB at the end of the first wave of the Spain COVID-19 pandemic was high, and large proportions of STB are potentially attributable to mental disorders and adverse events-experiences related to the pandemic, including health-related stress, lack of social support and interpersonal stress. There is an urgent need to allocate resources to increase access to adequate mental healthcare, even in times of healthcare system overload. This study was supported by the Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación/FEDER (grant number COV20/00711), (PM, grant number ISCIII, CD18/00049), (grant number ISCIII, FI18/00012), (VPS, grant number PI19/00236); Ayudas para la Formación de Profesorado Universitario, Ministerio de Ciencia, Innovación y Universidades (grant number FPU15/05728); Generalitat de Catalunya (grant number 2017SGR452). The funding institutions had no role in the design, analysis, interpretation or submission of publication of the data. No payment was made for writing this article by a pharmaceutical company or other agency. Corresponding authors had full access to all the data in the study and the final responsibility for the decision of submitting for publication. Sí

Background Caregivers of patients with chronic conditions or disability experience fatigue, burden and poor health-related quality of life. There is evidence of the effectiveness of support interventions for decreasing this impact. However, little is known about the benefits of home-based nursing intervention in primary health care. Objectives To evaluate the effectiveness of a home-based, nurse-led-intervention (CuidaCare) on the quality of life of caregivers of individuals with disabilities or chronic conditions living in the community, measured at 12-month follow-up. Methods A pragmatic, two-arm, cluster-randomized controlled trial with a 1-year follow-up period was performed between June 2013 and December 2015. Consecutive caregivers aged 65 years or older, all of whom assumed the primary responsibility of caring for people with disabling conditions for at least 6 months a year, were recruited from 22 primary health care centers. Subsequently, 11 centers were randomly assigned to usual care group, and 11 were assigned to the intervention group. The caregivers in the intervention group received the usual care and additional support (cognitive restructuring, health education and emotional support). The primary outcome was quality of life, assessed with the EQ-5D instrument (visual analog scale and utility index score); the secondary outcome variables were perception of burden, anxiety, and depression. Data were collected at baseline, at the end of the intervention, and at the 6- and 12-month follow-up visits. We analyzed the primary outcome as intention-to-treat, and missing data were added using the conditional mean single imputation method. Results A total of 224 caregivers were included in the study (102 in the intervention group and 122 in the usual care group). Generalized Estimating Equation models showed that the CuidaCare intervention was associated with a 5.46 point (95% CI: 2.57; 8.35) change in the quality of life, as measured with the visual analog scale adjusted for the rest of the variables at 12 months. It also produced an increase of 0.04 point (95% CI: 0.01; 0.07) in the utilities. No statistically significant differences were found between the two groups at 12 months with respect to the secondary outcomes. Conclusions The findings suggest that incorporating a home-based, nurse-led-intervention for caregivers into primary care can improve the health-related quality of life of caregivers of patients with chronic or disabling conditions.

Few economic evaluations have assessed laparoscopy for colon cancer. This study aimed to compare the cost-effectiveness of laparoscopic and open surgery for the treatment of colon cancer. A cost-effectiveness analysis was performed comparing two groups of patients treated according to standard clinical practice (REDISSEC-CARESS/CCR cohort) by laparoscopic or open surgery. Data were collected from health records on clinical characteristics and resource use over 2 years after surgery. To calculate the incremental cost-effectiveness ratio, costs and quality-adjusted life years (QALYs) were obtained for each patient. Clinical heterogeneity was addressed using propensity score and joint multivariable analysis (seemingly unrelated regression) that included interactions between TNM stage, age, and surgical procedure to perform subgroup analysis. The sample was composed of 1591 patients, 963 who underwent laparoscopy and 628 open surgery. Using propensity score and regression analysis, we found that laparoscopy was associated with more QALYs and less resource use than open surgery (0.0163 QALYs, 95% CI 0.0114–0.0212; and − €3461, 95% CI − 3337 to − 3586). Costs were lower for laparoscopy in all subgroups. In the subgroups younger than 80 years old, utility was higher in patients who underwent laparoscopy. Nevertheless, open surgery had better outcomes in older patients in stages I–II (0.0618 QALYs) and IV (0.5090 QALYs). Overall, laparoscopy appears to be dominant, resulting in more QALYs and lower costs. Nevertheless, while laparoscopy required fewer resources in all subgroups, outcomes may be negatively affected in elderly patients, representing an opportunity for shared decision making between surgeons and patients. ClinicalTrials.gov Identifier: NCT02488161

Background Multimorbidity is a global health challenge that is associated with polypharmacy, increasing the risk of potentially inappropriate prescribing (PIP). There are tools to improve prescription, such as implicit and explicit criteria. Objective To estimate the prevalence of PIP in a population aged 65 to 74 years with multimorbidity and polypharmacy, according to American Geriatrics Society Beers Criteria® (2015, 2019), the Screening Tool of Older Person’s Prescription -STOPP- criteria (2008, 2014), and the Medication Appropriateness Index -MAI- criteria in primary care. Methods This was an observational, descriptive, cross-sectional study. The sample included 593 community-dwelling elderly aged 65 to 74 years, with multimorbidity and polypharmacy, who participated in the MULTIPAP trial. Socio-demographic, clinical, professional, and pharmacological-treatment variables were recorded. Potentially inappropriate prescribing was detected by computerized prescription assistance system, and family doctors evaluated the MAI. The MAI-associated factors were analysed using a logistic regression model. Results A total of 4,386 prescriptions were evaluated. The mean number of drugs was 7.4 (2.4 SD). A total of 94.1% of the patients in the study had at least one criterion for drug inappropriateness according to the MAI. Potentially inappropriate prescribing was detected in 57.7%, 43.6%, 68.8% and 71% of 50 patients according to the explicit criteria STOPP 2014, STOPP 2008, Beers 2019 and Beers 2015 respectively. For every new drug taken by a patient, the MAI score increased by 2.41 (95% CI 1.46; 3.35) points. Diabetes, ischaemic heart disease and asthma were independently associated with lower summated MAI scores. Conclusions The prevalence of potentially inappropriate prescribing detected in the sample was high and in agreement with previous literature for populations with multimorbidity and polypharmacy. The MAI criteria detected greater inappropriateness than did the explicit criteria, but their application was more complex and difficult to automate. Publisher PDF

ObjectiveTo estimate the prevalence of nonadherence to treatment and its relationship with social support and social context in patients with multimorbidity and polypharmacy followed-up in primary care.MethodsThis was an observational, descriptive, cross-sectional, multicenter study with an analytical approach. A total of 593 patients between 65-74 years of age with multimorbidity (≥3 diseases) and polypharmacy (≥5 drugs) during the last three months and agreed to participate in the MULTIPAP Study. The main variable was adherence (Morisky-Green). The predictors were social support (structural support and functional support (DUFSS)); sociodemographic variables; indicators of urban objective vulnerability; health-related quality of life (EQ-5D-5L-VAS & QALY); and clinical variables. Descriptive, bivariate and multivariate analyses with logistic regression models and robust estimators were performed.ResultsFour out of ten patients were nonadherent, 47% had not completed primary education, 28.7% had an income ≤1050 €/month, 35% reported four or more IUVs, and the average perceived health-related quality of life (HRQOL) EQ-5D-5L-VAS was 65.5. The items that measure functional support, with significantly different means between nonadherent and adherent patients were receiving love and affection (-0.23; 95%CI: -0.40;-0.06), help when ill (-0.25; 95%CI: -0.42;-0.08), useful advice (-0.20; 95%CI: -0.37;-0.02), social invitations (-0.22; 95%CI:-0.44;-0.01), and recognition (-0.29; 95%CI:-0.50;-0.08). Factors associated with nonadherence were belonging to the medium vs. low tertile of functional support (0.62; 95%CI: 0.42;0.94), reporting less than four IUVs (0.69; 95%CI: 0.46;1.02) and higher HRQOL perception (0.98; 95%CI: 0.98;0.99).ConclusionsAmong patients 65-74 years of age with multimorbidity and polypharmacy, lower functional support was related to nonadherence to treatment. The nonadherence decreased in those patients with higher functional support, lower urban vulnerability and higher perceived health status according to the visual analog scale of health-related quality of life.

To assess the impact of readmission and reoperation on colon or rectal cancer patients in clinical and patient-reported outcome measures (PROMs) and to identify predictors of these events up to 1 year after surgery. Prospective cohort study of patients diagnosed with colon or rectal cancer who underwent surgery at 1 of 22 hospitals. Medical history, clinical parameters, and PROMs were evaluated as possible predictors. Multivariable multilevel logistic regression and survival models were used in the analyses to create the clinical prediction rules. Models were developed in a derivation sample and validated in a different sample. Readmission and reoperation were related to clinical outcomes and changes in some PROMs. Predictors of readmission in colon cancer were ASA class (odds ratio (OR) 4.5), TNM (OR for TNM III 3.24, TNM IV 4.55), evidence of residual tumor (R2) (OR 3.96), and medical (OR 1.96) and infectious (OR 2.01) complications within 30 days after surgery, while for rectal cancer, the predictors identified were age (OR 1.03), R2 (OR 6.48), infectious complications within 30 days (OR 2.29), hemoglobin (OR 3.26), lymph node ratio (OR 2.35), and surgical complications within 1 month (OR 3.04). Predictors of reoperation were TNM IV (OR 5.06), surgical complications within 30 days (OR 1.98), and type and site of tumor (OR 1.72) in colon cancer and being male (OR 1.52), age (OR 1.80), stoma (OR 1.87), and surgical complications within 1 month (OR 1.95) in rectal cancer. Our clinical prediction rule models are easy to use and could help to develop and implement interventions to reduce preventable readmissions and reoperations. https://clinicaltrials.gov/ct2/show/NCT02488161 Identifier: NCT02488161

Background: To validate and recalibrate the CR- POSSUM model and compared its discriminatory capacity with other European models such as POSSUM, P-POSSUM, AFC or IRCS to predict operative mortality in surgery for colorectal cancer. Methods: Prospective multicenter cohort study from 22 hospitals in Spain. We included patients undergoing planned or urgent surgery for primary invasive colorectal cancers between June 2010 and December 2012 (N = 2749). Clinical data were gathered through medical chart review. We validated and recalibrated the predictive models using logistic regression techniques. To calculate the discriminatory power of each model, we estimated the areas under the curve - AUC (95% CI). We also assessed the calibration of the models by applying the Hosmer-Lemeshow test. Results: In-hospital mortality was 1.5% and 30-day mortality, 1.7%. In the validation process, the discriminatory power of the CR-POSSUM for predicting in-hospital mortality was 73.6%. However, in the recalibration process, the AUCs improved slightly: the CR-POSSUM reached 75.5% (95% CI: 67.3–83.7). The discriminatory power of the CR-POSSUM for predicting 30-day mortality was 74.2% (95% CI: 67.1–81.2) after recalibration; among the other models the POSSUM had the greatest discriminatory power, with an AUC of 77.0% (95% CI: 68.9–85.2). The Hosmer-Lemeshow test showed good fit for all the recalibrated models. Conclusion: The CR-POSSUM and the other models showed moderate capacity to discriminate the risk of operative mortality in our context, where the actual operative mortality is low. Nevertheless the IRCS might better predict in-hospital mortality, with fewer variables, while the CR-POSSUM could be slightly better for predicting 30-day mortality, This work was supported in part by grants from the Fondo de Investigación Sanitaria (PS09/00314, PS09/00910, PS09/00746, PS09/00805, PI09/90460, PI09/90490, PI09/90397, PI09/90453, PI09/90441); The Department of Health of the Basque Country (2010111098); KRONIKGUNE –Centro de Investigación en Cronicidad (KRONIK 11/006); and the European Regional Development Fund (ERDF); and the thematic networks - REDISSEC (Health Services Research on Chronic Diseases Network; RD12/0001/0007) – of the Instituto de Salud Carlos III

The REDISSEC CARESS-CCR (Results and Health Services Research in Colorectal Cancer)- group: Jose María Quintana, Marisa Baré, Maximino Redondo, Eduardo Briones, Nerea Fernández de Larrea, Cristina Sarasqueta, Antonio Escobar, Francisco Rivas, Maria M. Morales-Suárez, Juan Antonio Blasco, Isabel del Cura, Inmaculada Arostegui, Amaia Bilbao, Nerea González, Susana García-Gutiérrez, Iratxe Lafuente, Urko Aguirre, Miren Orive, Josune Martin, Ane Antón-Ladislao, Núria Torà, Marina Pont, María Purificación Martínez del Prado, Alberto Loizate, Ignacio Zabalza, José Errasti, Antonio Z Gimeno, Santiago Lázaro, Mercè Comas, Jose María Enríquez, Carlos Placer, Amaia Perales, Iñaki Urkidi, Jose María Erro, Enrique Cormenzana, Adelaida Lacasta, Pep Piera Pibernat, Elena Campano, Ana Isabel Sotelo, Segundo Gómez-Abril, F. Medina-Cano, Julia Alcaide, Arturo Del Rey-Moreno, Manuel Jesús Alcántara, Rafael Campo, Alex Casalots, Carles Pericay, Maria José Gil, Miquel Pera, Pablo Collera, Josep Alfons Espinàs, Mercedes Martínez, Mireia Espallargues, Caridad Almazán, Paula Dujovne Lindenbaum, José María Fernández-Cebrián, Rocío Anula Fernández, Julio Ángel Mayol, Ramón Cantero, Héctor Guadalajara, María Heras, Damián García, Mariel Morey, Javier Mar., [Background] Colorectal cancers are one of the most common forms of malignancy worldwide. But two significant areas of research less studied deserve attention: health services use and development of patient stratification risk tools for these patients., [Methods] Design: a prospective multicenter cohort study with a follow up period of up to 5 years after surgical intervention. Participant centers: 22 hospitals representing six autonomous communities of Spain. Participants/Study population: Patients diagnosed with colorectal cancer that have undergone surgical intervention and have consented to participate in the study between June 2010 and December 2012. Variables collected include pre-intervention background, sociodemographic parameters, hospital admission records, biological and clinical parameters, treatment information, and outcomes up to 5 years after surgical intervention. Patients completed the following questionnaires prior to surgery and in the follow up period: EuroQol-5D, EORTC QLQ-C30 (The European Organization for Research and Treatment of Cancer quality of life questionnaire) and QLQ-CR29 (module for colorectal cancer), the Duke Functional Social Support Questionnaire, the Hospital Anxiety and Depression Scale, and the Barthel Index. The main endpoints of the study are mortality, tumor recurrence, major complications, readmissions, and changes in health-related quality of life at 30 days and at 1, 2, 3 and 5 years after surgical intervention. Statistical analysis: In relation to the different endpoints, predictive models will be used by means of multivariate logistic models, Cox or linear mixed-effects regression models. Simulation models for the prediction of discrete events in the long term will also be used, and an economic evaluation of different treatment strategies will be performed through the use of generalized linear models., [Discussion] The identification of potential risk factors for adverse events may help clinicians in the clinical decision making process. Also, the follow up by 5 years of this large cohort of patients may provide useful information to answer different health services research questions., [Trial registration] ClinicalTrials.gov Identifier: NCT02488161. Registration date: June 16, 2015., This work was supported in part by grants from the Fondo de Investigación Sanitaria (PS09/00314, PS09/00910, PS09/00746, PS09/00805, PI09/90460, PI09/90490, PI09/90397, PI09/90453, PI09/90441); Department of Health of the Basque Country (2010111098); KRONIKGUNE –Centro de Investigación en Cronicidad (KRONIK 11/006); and the European Regional Development Fund (ERDF).