63 research outputs found
Prevalence and natural history of potential coeliac disease in adult patients.
OBJECTIVE:
Potential celiac disease (PCD) is a form of CD characterized by positive endomysial/tissue transglutaminase antibodies and a preserved duodenal mucosa despite a gluten-containing diet (GCD); it can evolve into flat, active CD. This evolution is, however, not certain. Our aim was to retrospectively study the prevalence and the natural history of adult patients with PCD.
METHODS:
The clinical notes of all 47 patients with PCD attending our clinic between September 1999 and October 2011 were retrospectively reevaluated. To study their clinical features, patients with active CD, randomly selected and matched for sex and date of birth, served as controls. Symptoms, associated diseases, familiarity, and laboratory data at diagnosis were compared.
RESULTS:
Prevalence of PCD among all celiac patients directly diagnosed in our center was 42/187, (1/4.4, 18.3%, 95% confidence interval (CI) 13.3-23.4%). Age at diagnosis, laboratory data, prevalence of symptoms, associated diseases, and familiarity for CD did not differ between patients with PCD and those with active CD. Some patients with PCD maintained a normal duodenal mucosa for many years and their symptoms spontaneously improved despite maintaining a GCD.
CONCLUSIONS:
PCD is not a rare form of CD. Having found no difference at all in age at diagnosis and clinical features between PCD and active CD could suggest that PCD is not a prodrome of CD but is a separate entity that can only subsequently evolve into active CD
Characteristics of the colorectal cancers diagnosed in the early 2000s in Italy. Figures from the IMPATTO study on colorectal cancer screening
The impact of organized screening programmes on colorectal cancer (CRC) can be observed at a population level only several years after the implementation of screening. We compared CRC characteristics by diagnostic modality (screen-detected, non-screen-detected) as an early outcome to monitor screening programme effectiveness. Data on CRCs diagnosed in Italy from 2000 to 2008 were collected by several cancer registries. Linkage with screening datasets made it possible to divide the cases by geographic area, implementation of screening, and modality of diagnosis (screen-detected, non-screen-detected).We compared the main characteristics of the different subgroups of CRCs through multivariate logistic regression models. The study included 23,668 CRCs diagnosed in subjects aged 50-69 years, of which 11.9%were screendetected (N=2,806), all from the North-Centre of Italy. Among screen-detected CRCs, we observed a higher proportion of males, of cases in the distal colon, and a higher mean age of the patients. Compared with pre-screening cases, screen-detected CRCs showed a better distribution by stage at diagnosis (OR for stage III or IV: 0.40, 95%CI: 0.36-0.44) and grading (OR for poorly differentiated CRCs was 0.86, 95%CI: 0.75-1.00). Screen-detected CRCs have more favourable prognostic characteristics than non-screen-detected cases. A renewed effort to implement screening programmes throughout the entire country is recommended
Incidence trends of colorectal cancer in the early 2000s in Italy. Figures from the IMPATTO study on colorectal cancer screening
We utilised the IMPATTO study's archives to describe the 2000-2008 colorectal cancer (CRC) incidence rate trends in Italy, once screening programmes based on the faecal immunochemical test were implemented in different areas. Data on CRCs diagnosed in Italy from 2000 to 2008 in subjects aged 40-79 years were collected by 23 cancer registries. Incidence rate trends were evaluated as a whole and by macro-area (North-Centre and South-Islands), presence of a screening programme, sex, ten-year age class, anatomic site, stage at diagnosis, and pattern of diagnosis (screen-detected, non-screen-detected). The annual percent change (APC) of incidence rate trends, with 95% confidence intervals (95%CI), were computed. The study included 46,857 CRCs diagnosed in subjects aged 40-79 years, of which 2,806 were screendetected. The incidence rates in the North-Centre were higher than in the South and on the Islands. During the study period, screening programmes had been implemented only in the North-Centre and had a significant effect on incidence rates, with an initial sharp increase in incidence, followed by a decrease that started in the 3rd-4th years of screening. These incidence rate trends were exclusively due to modifications in the rates of stage I cases. After screening programmes started, incidence increased in all anatomic sites, particularly in the distal colon. The differential figures introduced by the implementation of screening programmes warrant a continuous surveillance of CRC incidence and mortality trends to monitor the impact of screening at a national level
ITALIAN CANCER FIGURES - REPORT 2015: The burden of rare cancers in Italy = I TUMORI IN ITALIA - RAPPORTO 2015: I tumori rari in Italia
OBJECTIVES:
This collaborative study, based on data collected by the network of Italian Cancer Registries (AIRTUM), describes the burden of rare cancers in Italy. Estimated number of new rare cancer cases yearly diagnosed (incidence), proportion of patients alive after diagnosis (survival), and estimated number of people still alive after a new cancer diagnosis (prevalence) are provided for about 200 different cancer entities.
MATERIALS AND METHODS:
Data herein presented were provided by AIRTUM population- based cancer registries (CRs), covering nowadays 52% of the Italian population. This monograph uses the AIRTUM database (January 2015), which includes all malignant cancer cases diagnosed between 1976 and 2010. All cases are coded according to the International Classification of Diseases for Oncology (ICD-O-3). Data underwent standard quality checks (described in the AIRTUM data management protocol) and were checked against rare-cancer specific quality indicators proposed and published by RARECARE and HAEMACARE (www.rarecarenet.eu; www.haemacare.eu). The definition and list of rare cancers proposed by the RARECAREnet "Information Network on Rare Cancers" project were adopted: rare cancers are entities (defined as a combination of topographical and morphological codes of the ICD-O-3) having an incidence rate of less than 6 per 100,000 per year in the European population. This monograph presents 198 rare cancers grouped in 14 major groups. Crude incidence rates were estimated as the number of all new cancers occurring in 2000-2010 divided by the overall population at risk, for males and females (also for gender-specific tumours).The proportion of rare cancers out of the total cancers (rare and common) by site was also calculated. Incidence rates by sex and age are reported. The expected number of new cases in 2015 in Italy was estimated assuming the incidence in Italy to be the same as in the AIRTUM area. One- and 5-year relative survival estimates of cases aged 0-99 years diagnosed between 2000 and 2008 in the AIRTUM database, and followed up to 31 December 2009, were calculated using complete cohort survival analysis. To estimate the observed prevalence in Italy, incidence and follow-up data from 11 CRs for the period 1992-2006 were used, with a prevalence index date of 1 January 2007. Observed prevalence in the general population was disentangled by time prior to the reference date (≤2 years, 2-5 years, ≤15 years). To calculate the complete prevalence proportion at 1 January 2007 in Italy, the 15-year observed prevalence was corrected by the completeness index, in order to account for those cancer survivors diagnosed before the cancer registry activity started. The completeness index by cancer and age was obtained by means of statistical regression models, using incidence and survival data available in the European RARECAREnet data.
RESULTS:
In total, 339,403 tumours were included in the incidence analysis. The annual incidence rate (IR) of all 198 rare cancers in the period 2000-2010 was 147 per 100,000 per year, corresponding to about 89,000 new diagnoses in Italy each year, accounting for 25% of all cancer. Five cancers, rare at European level, were not rare in Italy because their IR was higher than 6 per 100,000; these tumours were: diffuse large B-cell lymphoma and squamous cell carcinoma of larynx (whose IRs in Italy were 7 per 100,000), multiple myeloma (IR: 8 per 100,000), hepatocellular carcinoma (IR: 9 per 100,000) and carcinoma of thyroid gland (IR: 14 per 100,000). Among the remaining 193 rare cancers, more than two thirds (No. 139) had an annual IR <0.5 per 100,000, accounting for about 7,100 new cancers cases; for 25 cancer types, the IR ranged between 0.5 and 1 per 100,000, accounting for about 10,000 new diagnoses; while for 29 cancer types the IR was between 1 and 6 per 100,000, accounting for about 41,000 new cancer cases. Among all rare cancers diagnosed in Italy, 7% were rare haematological diseases (IR: 41 per 100,000), 18% were solid rare cancers. Among the latter, the rare epithelial tumours of the digestive system were the most common (23%, IR: 26 per 100,000), followed by epithelial tumours of head and neck (17%, IR: 19) and rare cancers of the female genital system (17%, IR: 17), endocrine tumours (13% including thyroid carcinomas and less than 1% with an IR of 0.4 excluding thyroid carcinomas), sarcomas (8%, IR: 9 per 100,000), central nervous system tumours and rare epithelial tumours of the thoracic cavity (5%with an IR equal to 6 and 5 per 100,000, respectively). The remaining (rare male genital tumours, IR: 4 per 100,000; tumours of eye, IR: 0.7 per 100,000; neuroendocrine tumours, IR: 4 per 100,000; embryonal tumours, IR: 0.4 per 100,000; rare skin tumours and malignant melanoma of mucosae, IR: 0.8 per 100,000) each constituted <4% of all solid rare cancers. Patients with rare cancers were on average younger than those with common cancers. Essentially, all childhood cancers were rare, while after age 40 years, the common cancers (breast, prostate, colon, rectum, and lung) became increasingly more frequent. For 254,821 rare cancers diagnosed in 2000-2008, 5-year RS was on average 55%, lower than the corresponding figures for patients with common cancers (68%). RS was lower for rare cancers than for common cancers at 1 year and continued to diverge up to 3 years, while the gap remained constant from 3 to 5 years after diagnosis. For rare and common cancers, survival decreased with increasing age. Five-year RS was similar and high for both rare and common cancers up to 54 years; it decreased with age, especially after 54 years, with the elderly (75+ years) having a 37% and 20% lower survival than those aged 55-64 years for rare and common cancers, respectively. We estimated that about 900,000 people were alive in Italy with a previous diagnosis of a rare cancer in 2010 (prevalence). The highest prevalence was observed for rare haematological diseases (278 per 100,000) and rare tumours of the female genital system (265 per 100,000). Very low prevalence (<10 prt 100,000) was observed for rare epithelial skin cancers, for rare epithelial tumours of the digestive system and rare epithelial tumours of the thoracic cavity.
COMMENTS:
One in four cancers cases diagnosed in Italy is a rare cancer, in agreement with estimates of 24% calculated in Europe overall. In Italy, the group of all rare cancers combined, include 5 cancer types with an IR>6 per 100,000 in Italy, in particular thyroid cancer (IR: 14 per 100,000).The exclusion of thyroid carcinoma from rare cancers reduces the proportion of them in Italy in 2010 to 22%. Differences in incidence across population can be due to the different distribution of risk factors (whether environmental, lifestyle, occupational, or genetic), heterogeneous diagnostic intensity activity, as well as different diagnostic capacity; moreover heterogeneity in accuracy of registration may determine some minor differences in the account of rare cancers. Rare cancers had worse prognosis than common cancers at 1, 3, and 5 years from diagnosis. Differences between rare and common cancers were small 1 year after diagnosis, but survival for rare cancers declined more markedly thereafter, consistent with the idea that treatments for rare cancers are less effective than those for common cancers. However, differences in stage at diagnosis could not be excluded, as 1- and 3-year RS for rare cancers was lower than the corresponding figures for common cancers. Moreover, rare cancers include many cancer entities with a bad prognosis (5-year RS <50%): cancer of head and neck, oesophagus, small intestine, ovary, brain, biliary tract, liver, pleura, multiple myeloma, acute myeloid and lymphatic leukaemia; in contrast, most common cancer cases are breast, prostate, and colorectal cancers, which have a good prognosis. The high prevalence observed for rare haematological diseases and rare tumours of the female genital system is due to their high incidence (the majority of haematological diseases are rare and gynaecological cancers added up to fairly high incidence rates) and relatively good prognosis. The low prevalence of rare epithelial tumours of the digestive system was due to the low survival rates of the majority of tumours included in this group (oesophagus, stomach, small intestine, pancreas, and liver), regardless of the high incidence rate of rare epithelial cancers of these sites. This AIRTUM study confirms that rare cancers are a major public health problem in Italy and provides quantitative estimations, for the first time in Italy, to a problem long known to exist. This monograph provides detailed epidemiologic indicators for almost 200 rare cancers, the majority of which (72%) are very rare (IR<0.5 per 100,000). These data are of major interest for different stakeholders. Health care planners can find useful information herein to properly plan and think of how to reorganise health care services. Researchers now have numbers to design clinical trials considering alternative study designs and statistical approaches. Population-based cancer registries with good quality data are the best source of information to describe the rare cancer burden in a population
A second duodenal biopsy is necessary in the follow-up of adult coeliac patients.
INTRODUCTION:
Coeliac disease is a chronic enteropathy requiring a close follow-up. However, the best way to follow up coeliac patients has not yet been established. In the last 14 years, we have been offering patients a thorough series of periodical examinations including a histological re-evaluation at 12-18 months.
PATIENTS AND METHODS:
The notes of all coeliac patients attending our clinic between September 1999 and March 2013 were examined.
RESULTS:
Data from 317 adult patients were collected. Duodenal biopsy showed a lack of satisfactory histological response in 25/317 patients; endomysial antibodies were still positive in 76, and diet adherence and clinical response were unsatisfactory in 58 and 97, respectively. Correlations of serological data, clinical response, and diet adherence with histological findings were evaluated. Although the P values showed statistically significant differences, sensitivity and specificity were disappointing: 64% and 80% for serological response, 48% and 71% for clinical response, 56% and 85% for diet adherence.
CONCLUSIONS:
After 12-18 months on a gluten-free diet, 8% of the patients do not present a satisfactory histological response; only some of them could have been identified with a serological and/or clinical re-evaluation. Therefore, a duodenal biopsy seems to be the only tool that could identify patients with unsatisfactory histological response
The influence of HLA-DQ2 and DQ8 on severity in celiac disease
BACKGROUND: HLA-DQB1*02 homozygosity was shown to be more common in patients with complicated rather than uncomplicated celiac disease (CD).
GOALS: To study HLA-DQA1 and DQB1 profile in adult patients with different forms of CD, including patients with complicated and potential CD, the most affected and the most preserved histologic end of the pathologic celiac spectrum.
STUDY: HLA-DQA1 and DQB1 molecula typing was performed in 218 adult CD patients (169 with uncomplicated CD, 27 with complicated CD, and 22 with potential CD) and 224 healthy stem cell donors, HLA-DQA1 and DQB1 gene polyporphism wa sanalyzed using polymerase chain reaction sequence-specific primers and/or reverse polymerase chain reaction sequence-specific oligonucleotides techniques.
RESULTS: As expected, the frequency of HLA-DQB1* allele, DQB1*02 homozygosity, and DQB1*0302 gene were statistically different in the 4 groups. However, multivariate analysis demonstrated that patients with potential CD have a higher frequency of both HLA-DQB1*0302 and HLA-DQB1*0603 alleles and a reduced frequency of DQB1*02 homozygosity compared with patients with uncomplicated and complicated CD.
CONCLUSIONS: The increased frequency of DQB1*0302 and the reduced frequency of DQB1*02 homozygosity in potential CD is consistent with the idea that different clinical/pathologic evolutions might be related to different immunogeneses. This could be clinically relevant in the future
Using mechanistic model-based inference to understand and project epidemic dynamics with time-varying contact and vaccination rates
Abstract Epidemiological models range in complexity from relatively simple statistical models that make minimal assumptions about the variables driving epidemic dynamics to more mechanistic models that include effects such as vaccine-derived and infection-derived immunity, population structure and heterogeneity. The former are often fitted to data in real-time and used for short-term forecasting, while the latter are more suitable for comparing longer-term scenarios under differing assumptions about control measures or other factors. Here, we present a mechanistic model of intermediate complexity that can be fitted to data in real-time but is also suitable for investigating longer-term dynamics. Our approach provides a bridge between primarily empirical approaches to forecasting and assumption-driven scenario models. The model was developed as a policy advice tool for New Zealand’s 2021 outbreak of the Delta variant of SARS-CoV-2 and includes the effects of age structure, non-pharmaceutical interventions, and the ongoing vaccine rollout occurring during the time period studied. We use an approximate Bayesian computation approach to infer the time-varying transmission coefficient from real-time data on reported cases. We then compare projections of the model with future, out-of-sample data. We find that this approach produces a good fit with in-sample data and reasonable forward projections given the inherent limitations of predicting epidemic dynamics during periods of rapidly changing policy and behaviour. Results from the model helped inform the New Zealand Government’s policy response throughout the outbreak
- …