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BACKGROUND: The incidence of comorbidities is higher in HIV-positive patients than in the general population due to factors, such as HIV-related chronic inflammation. There is no consensus on whether a low CD4 lymphocyte count after virological suppression at long-term follow-up increases the risk of comorbidities. This study evaluates the association between CD4 lymphocyte count and the incidence of comorbidities during the first 5 years of virological suppression after highly active antiretroviral treatment. METHODS: We conducted a cohort study of HIV-positive adults who achieved virological suppression in an HIV program between 2002 and 2016 in Colombia. A generalized equation estimation model was used to estimate the association between CD4 lymphocyte count and the incidence of comorbidities. RESULTS: A follow-up period of at least 1 year was completed in 921 HIV-positive patients with virological suppression. We found 71 comorbidities during a maximum of 5 years of follow-up; 41 (59%) were AIDS-defining comorbidities and 19 (46%) of them occurred during the first semester. Thirty cases of non-AIDS- defining comorbidities were diagnosed.We did not find any association between CD4 lymphocyte count and the incidence of comorbidities (OR 0.92, CI 95% 0.45 -1.91 for CD4 201-499 cells/µL vs CD4 ≤200 cells/µL, and OR 0.55, 95% CI 0.21-1.44 for CD4 ≥500 cells/µL vs CD4 ≤200 cells/µL). CONCLUSION: No association was found between CD4 lymphocyte count and the incidence of AIDS-defining or non-AIDS-defining comorbidities in patients with virological suppression. Further studies are needed to assess the risk of comorbidities in this population to design interventions aimed at improving their prognosis.

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BACKGROUND: Childhood leukemia (CL) is the most prevalent form of pediatric cancer on a global scale. However, there is a limited understanding of the dynamics of CL incidence in South America, with a specific knowledge gap in Colombia. This study aimed to identify trends in CL incidence and to analyze the effects of age, period, and birth cohort on the risk of leukemia incidence in this population. METHODS: Information on all newly diagnosed leukemia cases (in general and by subtype) among residents aged 0-18 years and living in the serving areas of population-based cancer registries of Cali (2008-2017), Bucaramanga (2000-2017), Manizales (2003-2017), and Pasto (1998-2018). Estimated annual percent changes (EAPC) in incidence over time and potential changes in the slope of these EAPCs were calculated using joinpoint regression models. The effects of age, period, and cohort in CL incidence trends were evaluated using age-period-cohort models addressing the identifiability issue through the application of double differences. RESULTS: A total of 966 childhood leukemia cases were identified. The average standardized incidence rate (ASIR) of leukemia was calculated and expressed per 100,000 person-years - observing ASIR of 4.46 in Cali, 7.27 in Bucaramanga, 3.89 in Manizales and 4.06 in Pasto. Concerning CL trends there were no statistically significant changes in EAPC throughout the different periods, however, when analyzed by leukemia subtype, statistically significant changes were observed in the EAPC for both ALL and AML. Analysis of age-period-cohort models revealed that age-related factors significantly underpin the incidence trends of childhood leukemia in these four Colombian cities. CONCLUSIONS: This study offers valuable insights into the incidence trends of childhood leukemia in four major Colombian cities. The analysis revealed stable overall CL incidence rates across varying periods, predominantly influenced by age-related factors and the absence of cohort and period effects. This information is useful for surveillance and planning purposes for CL diagnosis and treatment in Colombia.

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We aimed to improve the available information on morphology and stage for cutaneous melanoma in the population-based cancer registry of the Bucaramanga Metropolitan Area in Colombia. The incidence and survival rates and the distribution of melanoma patients by age, gender, anatomical subsite, and histological subtype were calculated. All 113 melanoma patients (median age 61) were followed up (median time 7.4 years). This exercise (filling in missing information in the registry by manual search of patient clinical record and other available information) yielded more identified invasive melanomas and cases with complete information on anatomical localization and stage. Age-standardized incidence and mortality rates were 1.86 and 1.08, being slightly higher for males. Most melanomas were localized on the lower limbs, followed by the trunk. For 35% of all melanomas, the morphological subtype remained unknown. Most of the remaining melanomas were nodular and acral lentiginous melanomas. Overall global and relative 5-year survival was 61.6% and 71.3%, respectively, with poorer survival for males than females. Melanomas on the head and neck and unspecified anatomical sites had the worst survival. Patients without stage information in their medical files had excellent survival, unlike patients for whom medical files were no longer available. This study shows the possibility of improving data availability and the importance of good quality population-based data.

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Objectives: To quantify socioeconomic inequalities in COVID-19 mortality in Colombia and to assess the extent to which type of health insurance, comorbidity burden, area of residence, and ethnicity account for such inequalities. Methods: We analyzed data from a retrospective cohort of COVID-19 cases. We estimated the relative and slope indices of inequality (RII and SII) using survival models for all participants and stratified them by age and gender. We calculated the percentage reduction in RII and SII after adjustment for potentially relevant factors. Results: We identified significant inequalities for the whole cohort and by subgroups (age and gender). Inequalities were higher among younger adults and gradually decreased with age, going from RII of 5.65 (95% confidence interval [CI] = 3.25, 9.82) in participants younger than 25 years to RII of 1.49 (95% CI = 1.41, 1.58) in those aged 65 years and older. Type of health insurance was the most important factor, accounting for 20% and 59% of the relative and absolute inequalities, respectively. Conclusions: Significant socioeconomic inequalities exist in COVID-19 mortality in Colombia. Health insurance appears to be the main contributor to those inequalities, posing challenges for the design of public health strategies.

Objetivos: Quantificar as desigualdades socioeconômicas na mortalidade por COVID-19 na Colômbia e avaliar até que ponto o tipo de cobertura de assistência à saúde, a carga de comorbidades, o local de residência e a etnia contribuíram para tais desigualdades. Métodos: Analisamos dados de uma coorte retrospectiva de casos de COVID-19. Calculamos os índices relativo e angular de desigualdade (RII e SII, respectivamente) utilizando modelos de sobrevivência em todos os participantes, estratificando-os por idade e gênero. Calculamos o percentual de redução no RII e no SII após ajuste para fatores possivelmente relevantes. Resultados: Identificamos desigualdades significativas na coorte como um todo e por subgrupos (idade e gênero). As desigualdades foram maiores para adultos mais jovens e decaíram gradualmente com a idade, indo de um RII de 5,65 (intervalo de confiança [IC] de 95% = 3,25; 9,82] nos participantes com idade inferior a 25 anos a um RII de 1,49 [IC 95% = 1,41; 1,58] nas pessoas com 65 anos ou mais. O tipo de cobertura de assistência à saúde foi o fator mais importante, representando 20% e 59% das desigualdades relativa e absoluta, respectivamente. Conclusões: Desigualdades socioeconômicas significativas afetaram a mortalidade por COVID-19 na Colômbia. O tipo de cobertura de saúde parece ser o principal fator contribuinte para essas desigualdades, impondo desafios à elaboração de estratégias de saúde pública.

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Objectives. To quantify socioeconomic inequalities in COVID-19 mortality in Colombia and to assess the extent to which type of health insurance, comorbidity burden, area of residence, and ethnicity account for such inequalities. Methods. We analyzed data from a retrospective cohort of COVID-19 cases. We estimated the relative and slope indices of inequality (RII and SII) using survival models for all participants and stratified them by age and gender. We calculated the percentage reduction in RII and SII after adjustment for potentially relevant factors. Results. We identified significant inequalities for the whole cohort and by subgroups (age and gender). Inequalities were higher among younger adults and gradually decreased with age, going from RII of 5.65 (95% confidence interval [CI] = 3.25, 9.82) in participants younger than 25 years to RII of 1.49 (95% CI = 1.41, 1.58) in those aged 65 years and older. Type of health insurance was the most important factor, accounting for 20% and 59% of the relative and absolute inequalities, respectively. Conclusions. Significant socioeconomic inequalities exist in COVID-19 mortality in Colombia. Health insurance appears to be the main contributor to those inequalities, posing challenges for the design of public health strategies. (Am J Public Health. 2022;112(S6):S586-S590. https://doi.org/10.2105/AJPH.2021.306637).

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[RESUMEN]. Objetivo. Cuantificar las desigualdades socioeconómicas en la mortalidad por COVID-19 en Colombia y evaluar en qué medida el tipo de seguro de salud, la carga de enfermedades concomitantes, la zona de residencia y el origen étnico explican estas desigualdades. Métodos. Se analizaron los datos de una cohorte retrospectiva de casos de COVID-19. Se estimó el índice relativo de desigualdad (IRD) y el índice de desigualdad basado en la pendiente (IDP) utilizando modelos de supervivencia con todos los participantes, y estratificándolos por edad y sexo. El porcentaje de reducción del IRD y el IDP se calculó después de ajustar con respecto a factores que podrían ser relevantes. Resultados. Se pusieron en evidencia desigualdades notables en toda la cohorte y en los subgrupos (edad y sexo). Las desigualdades fueron mayores en los adultos más jóvenes y disminuyeron de manera gradual con la edad, pasando de un IRD de 5,65 (intervalo de confianza de 95% [IC 95%] = 3,25-9,82) en los participan- tes menores de 25 años a un IRD de 1,49 (IC 95% = 1,41-1,58) en los mayores de 65 años. El tipo de seguro de salud fue el factor más importante, al cual se atribuyó 20% de las desigualdades relativas y 59% de las absolutas. Conclusiones. La mortalidad por COVID-19 en Colombia presenta importantes desigualdades socioeconó- micas. El seguro de salud aparece como el factor que más contribuye a estas desigualdades, lo cual plantea retos al diseño de las estrategias de salud pública.

[ABSTRACT]. Objectives. To quantify socioeconomic inequalities in COVID-19 mortality in Colombia and to assess the extent to which type of health insurance, comorbidity burden, area of residence, and ethnicity account for such inequalities. Methods. We analyzed data from a retrospective cohort of COVID-19 cases. We estimated the relative and slope indices of inequality (RII and SII) using survival models for all participants and stratified them by age and gender. We calculated the percentage reduction in RII and SII after adjustment for potentially relevant factors. Results. We identified significant inequalities for the whole cohort and by subgroups (age and gender). Inequalities were higher among younger adults and gradually decreased with age, going from RII of 5.65 (95% confidence interval [CI] = 3.25, 9.82) in participants younger than 25 years to RII of 1.49 (95% CI = 1.41, 1.58) in those aged 65 years and older. Type of health insurance was the most important factor, accounting for 20% and 59% of the relative and absolute inequalities, respectively. Conclusions. Significant socioeconomic inequalities exist in COVID-19 mortality in Colombia. Health insu- rance appears to be the main contributor to those inequalities, posing challenges for the design of public health strategies.

[RESUMO]. Objetivos. Quantificar as desigualdades socioeconômicas na mortalidade por COVID-19 na Colômbia e ava- liar até que ponto o tipo de cobertura de assistência à saúde, a carga de comorbidades, o local de residência e a etnia contribuíram para tais desigualdades. Métodos. Analisamos dados de uma coorte retrospectiva de casos de COVID-19. Calculamos os índices relativo e angular de desigualdade (RII e SII, respectivamente) utilizando modelos de sobrevivência em todos os participantes, estratificando-os por idade e gênero. Calculamos o percentual de redução no RII e no SII após ajuste para fatores possivelmente relevantes. Resultados. Identificamos desigualdades significativas na coorte como um todo e por subgrupos (idade e gênero). As desigualdades foram maiores para adultos mais jovens e decaíram gradualmente com a idade, indo de um RII de 5,65 (intervalo de confiança [IC] de 95% = 3,25; 9,82] nos participantes com idade inferior a 25 anos a um RII de 1,49 [IC 95% = 1,41; 1,58] nas pessoas com 65 anos ou mais. O tipo de cobertura de assistência à saúde foi o fator mais importante, representando 20% e 59% das desigualdades relativa e absoluta, respectivamente. Conclusões. Desigualdades socioeconômicas significativas afetaram a mortalidade por COVID-19 na Colômbia. O tipo de cobertura de saúde parece ser o principal fator contribuinte para essas desigualdades, impondo desafios à elaboração de estratégias de saúde pública.

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BACKGROUND: Pathogenic germline mutations in the BRCA1 and BRCA2 (BRCA1/2) genes contribute to hereditary breast/ovarian cancer (OC) in White/mestizo Colombian women. As there is virtually no genetic data on breast cancer (BC) in Colombians of African descent, we conducted a comprehensive BRCA1/2 mutational analysis of 60 Afro-Colombian families affected by breast/OC. MATERIALS AND METHODS: Mutation screening of the complete BRCA1/2 genes for small-scale mutations and large genomic alterations was performed in these families using next-generation sequencing and multiplex ligation-dependent probe amplification analysis. RESULTS: Four pathogenic germline mutations, including one novel mutation, were identified, comprising 3 in BRCA1 and one in BRCA2. The prevalence of BRCA1/2 mutations, including one BRCA1 founder mutation (c.5123C>A) previously identified in this sample set, was 3.9% (2/51) in female BC-affected families and 33.3% (3/9) in those affected by both breast and OC. Haplotype analysis of 2 BRCA2_c.2701delC carriers (one Afro-Colombian and one previously identified White/mestizo Colombian patient with BC) suggested that the mutation arose in a common ancestor. CONCLUSION: Our data showed that 2/5 (40%) mutations (including the one previously identified in this sample set) are shared by White/mestizo Colombian and Afro-Colombian populations. This suggests that these 2 populations are closely related. Nevertheless, variations in the BRCA1/2 mutational spectrum among Afro-Colombian subgroups from different regions of the country were observed, suggesting that specific genetic risk assessment strategies need to be developed.

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BACKGROUND: Estimation of survival requires follow-up of patients from diagnosis until death ensuring complete and good quality data. Many population-based cancer registries in low- and middle-income countries have difficulties linking registry data with regional or national vital statistics, increasing the chances of cases lost to follow-up. The impact of lost to follow-up cases on survival estimates from small population-based cancer registries (<500 cases) has been understudied, and bias could be larger than in larger registries. METHODS: We simulated scenarios based on idealized real data from three population-based cancer registries to assess the impact of loss to follow-up on 1-5-year overall and net survival for stomach, colon, and thyroid cancers-cancer types with very different prognosis. Multiple scenarios with varying of lost to follow-up proportions (1-20%) and sample sizes of (100-500 cases) were carried out. We investigated the impact of excluding versus censoring lost to follow-up cases; punctual and bootstrap confidence intervals for the average bias are presented. RESULTS: Censoring of lost to follow-up cases lead to overestimation of the overall survival, this effect was strongest for cancers with a poor prognosis and increased with follow-up time and higher proportion of lost to follow-up cases; these effects were slightly larger for net survival than overall survival. Excluding cases lost to follow-up did not generate a bias on survival estimates on average, but in individual cases, there were under- and overestimating survival. For gastric, colon, and thyroid cancer, relative bias on 5-year cancer survival with 1% of lost to follow-up varied between 6% and 125%, 2% and 40%, and 0.1% and 1.0%, respectively. CONCLUSION: Estimation of cancer survival from small population-based registries must be interpreted with caution: even small proportions of censoring, or excluding lost to follow-up cases can inflate survival, making it hard to interpret comparison across regions or countries.

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RESUMEN Objetivo. Cuantificar las desigualdades socioeconómicas en la mortalidad por COVID-19 en Colombia y evaluar en qué medida el tipo de seguro de salud, la carga de enfermedades concomitantes, la zona de residencia y el origen étnico explican estas desigualdades. Métodos. Se analizaron los datos de una cohorte retrospectiva de casos de COVID-19. Se estimó el índice relativo de desigualdad (IRD) y el índice de desigualdad basado en la pendiente (IDP) utilizando modelos de supervivencia con todos los participantes, y estratificándolos por edad y sexo. El porcentaje de reducción del IRD y el IDP se calculó después de ajustar con respecto a factores que podrían ser relevantes. Resultados. Se pusieron en evidencia desigualdades notables en toda la cohorte y en los subgrupos (edad y sexo). Las desigualdades fueron mayores en los adultos más jóvenes y disminuyeron de manera gradual con la edad, pasando de un IRD de 5,65 (intervalo de confianza de 95% [IC 95%] = 3,25-9,82) en los participantes menores de 25 años a un IRD de 1,49 (IC 95% = 1,41-1,58) en los mayores de 65 años. El tipo de seguro de salud fue el factor más importante, al cual se atribuyó 20% de las desigualdades relativas y 59% de las absolutas. Conclusiones. La mortalidad por COVID-19 en Colombia presenta importantes desigualdades socioeconómicas. El seguro de salud aparece como el factor que más contribuye a estas desigualdades, lo cual plantea retos al diseño de las estrategias de salud pública.

ABSTRACT Objectives. To quantify socioeconomic inequalities in COVID-19 mortality in Colombia and to assess the extent to which type of health insurance, comorbidity burden, area of residence, and ethnicity account for such inequalities. Methods. We analyzed data from a retrospective cohort of COVID-19 cases. We estimated the relative and slope indices of inequality (RII and SII) using survival models for all participants and stratified them by age and gender. We calculated the percentage reduction in RII and SII after adjustment for potentially relevant factors. Results. We identified significant inequalities for the whole cohort and by subgroups (age and gender). Inequalities were higher among younger adults and gradually decreased with age, going from RII of 5.65 (95% confidence interval [CI] = 3.25, 9.82) in participants younger than 25 years to RII of 1.49 (95% CI = 1.41, 1.58) in those aged 65 years and older. Type of health insurance was the most important factor, accounting for 20% and 59% of the relative and absolute inequalities, respectively. Conclusions. Significant socioeconomic inequalities exist in COVID-19 mortality in Colombia. Health insurance appears to be the main contributor to those inequalities, posing challenges for the design of public health strategies.

RESUMO Objetivos. Quantificar as desigualdades socioeconômicas na mortalidade por COVID-19 na Colômbia e avaliar até que ponto o tipo de cobertura de assistência à saúde, a carga de comorbidades, o local de residência e a etnia contribuíram para tais desigualdades. Métodos. Analisamos dados de uma coorte retrospectiva de casos de COVID-19. Calculamos os índices relativo e angular de desigualdade (RII e SII, respectivamente) utilizando modelos de sobrevivência em todos os participantes, estratificando-os por idade e gênero. Calculamos o percentual de redução no RII e no SII após ajuste para fatores possivelmente relevantes. Resultados. Identificamos desigualdades significativas na coorte como um todo e por subgrupos (idade e gênero). As desigualdades foram maiores para adultos mais jovens e decaíram gradualmente com a idade, indo de um RII de 5,65 (intervalo de confiança [IC] de 95% = 3,25; 9,82] nos participantes com idade inferior a 25 anos a um RII de 1,49 [IC 95% = 1,41; 1,58] nas pessoas com 65 anos ou mais. O tipo de cobertura de assistência à saúde foi o fator mais importante, representando 20% e 59% das desigualdades relativa e absoluta, respectivamente. Conclusões. Desigualdades socioeconômicas significativas afetaram a mortalidade por COVID-19 na Colômbia. O tipo de cobertura de saúde parece ser o principal fator contribuinte para essas desigualdades, impondo desafios à elaboração de estratégias de saúde pública.

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BACKGROUND: In the area of nephrology, the practical application of relative survival methodologies can provide information regarding the impact of outcomes for patients with kidney failure on dialysis compared with what would be expected in the absence of this condition. OBJECTIVE: Compare the net survival of hemodialysis (HD) and peritoneal dialysis (PD) patients in a cohort of incident patients on chronic dialysis in Colombia, according to the dialysis therapy modality. DESIGN: Observational, analytic, historical cohort. SETTING: Renal Therapy Services (RTS) clinic network across Colombia. PATIENTS: Patients over 18 years old with chronic kidney disease, incidents in dialytic therapy, which reached day 90 of therapy. Recruitment took place from January 1, 2008, to December 31, 2013, with a follow-up until December 31, 2018. The final cohort for analysis corresponds to a total of 12 508 patients, of which 5330 patients (42.6%) began HD and 7178 patients (57.4%) began PD. MEASUREMENTS: Demographic, socioeconomic, and clinical variables were measured. METHODS: Analyses were conducted according to the treatment assigned (PD or HD) at the time of the inception of the cohort and another approach of analysis was done with a subsample of those patients who never changed the initial modality. To calculate expected survival, life tables were constructed for Colombia for the years 2006 to 2018. Net survival estimates were made using the Pohar Perme estimator. The comparison of the net survival curves was done using the method developed by Pavlic and Perme, the log-rank type. RESULTS: Net survival at 5 years compared with the general population was estimated at 0.53 (95% confidence interval 0.52-0.54) in the dialysis cohort. In intention-to-treat analyses of 7178 patients on PD and 5330 patients on HD, by global and Pohar-Perme methods, survival (expressed as a ratio of survival in patients on dialysis to survival in an age-, sex- and geographic-matched general Colombian population) was higher in patients on HD than in those on PD. In year 1, net survival by Pavlov-Perme on PD was 0.79 (95% confidence intervals [CI] 0.78 - 0.80) and on HD 0.85 (95% CI 0.84 - 0.86); in year 5, 0.36 (95% CI 0.34 - 0.38) and 0.57 (95% CI 0.55 - 0.59) for PD and HD respectively. LIMITATION: There may be imbalances among the populations analyzed (HD vs PD), in which one or more variables other than the type of therapy may influence the survival of the patients. In Colombia there are marginal levels of underreporting of demographic data in some subpopulations that may affect life-tables construction. CONCLUSION: An important difference was observed in terms of survival between the dialysis population and the population of reference without dialysis. Statistically significant differences were found in net survival between HD and PD, net survival was higher in patients on HD than in those on PD.

CONTEXTE: En néphrologie, l'application pratique des méthodologies de survie relative peut fournir des renseignements sur l'impact des résultats des patients atteints d'insuffisance rénale suivant des traitements de dialyse comparativement à ce qui serait attendu en l'absence de cette affection. OBJECTIF: Comparer la survie nette, selon la modalité de dialyse, dans une cohorte de patients colombiens traités par hémodialyse (HD) ou par dialyse péritonéale (DP) de façon chronique. TYPE D'ÉTUDE: Étude de cohorte observationnelle, analytique et historique. CADRE: Le réseau Renal Therapy Services (RTS) de la Colombie. SUJETS: Des patients adultes souffrant d'insuffisance chronique ayant nouvellement débuté la dialyse depuis plus de 90 jours. Le recrutement a eu lieu du 1er janvier 2008 au 31 décembre 2013, et le suivi s'est poursuivi jusqu'au 31 décembre 2018. L'analyse porte sur un total de 12 508 patients, dont 5 330 (42,6 %) avaient entrepris des traitements d'hémodialyse et 7 178 (57,4 %) de dialyse péritonéale. MESURES: Les données démographiques, socio-économiques et cliniques des patients. MÉTHODOLOGIE: Les analyses ont été menées en fonction du traitement attribué (DP ou HD) au moment de la création de la cohorte. Une autre analyse a été réalisée sur un sous-échantillon de patients n'ayant jamais changé la modalité depuis le début du traitement. Des tables de survie spécifiques à la Colombie entre les années 2006 et 2018 ont été élaborées pour calculer la survie attendue. Les estimations de survie nette ont été faites en utilisant l'estimateur de Pohar Perme. Et la méthode développée par Pavlic et Perme, soit le test du log-rank a servi à la comparaison des courbes de survie nette. RÉSULTATS: La survie nette après cinq ans, comparée à celle de la population générale, a été estimée à 0,53 (IC 95 %: 0,52 à 0,54) dans la cohorte de patients dialysés. Dans les analyses en intention de traiter portant sur 7 178 patients sous HD et 5 330 patients sous DP ­ réalisées par méthode globale et avec l'estimateur Pohar Perme ­ la survie (exprimée sous forme de rapport entre la survie de patients dialysés et la survie de Colombiens de la population générale du même âge, sexe et région géographique) s'est avérée plus élevée chez les patients sous HD que chez les patients sous DP. Au cours de la première année, la survie nette (Pavlov Perme) des patients sous DP s'établissait à 0,79 (IC 95 % : 0,78-0,80) et celle des patients sous HD à 0,85 (IC 95 % : 0,84-0,86); après cinq ans, elle était passée à 0,36 (IC 95 % : 0,34-0,38) pour les patients sous DP et à 0,57 (IC 95 % : 0,55-0,59) pour les patients sous HD. LIMITES: Il pourrait exister des disparités parmi les populations analysées (HD vs DP), où des variables autres que la modalité pourraient influencer la survie des patients. Il existe, dans certaines sous-populations de Colombie, des niveaux marginaux de sous-déclaration des données démographiques qui pourraient affecter l'élaboration des tables de survie. CONCLUSION: Une différence importante a été observée entre la survie des patients dialysés et celle d'une population de référence (personnes non dialysées). On a également constaté des différences statistiquement significatives entre le groupe sous HD et le groupe sous DP en ce qui concerne la survie nette, laquelle s'est avérée plus élevée chez les patients sous HD.