ReviewGastroenterology and hepatology from bed to bench2016
Burden of gastrointestinal cancers and problem of the incomplete information; how to make up the data?
Review in Gastroenterology and hepatology from bed to bench, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Phase Ib/II study of safety and efficacy of low-dose decitabine-primed chemoimmunotherapy in patients with drug-resistant relapsed/refractory alimentary tract cancer.International journal of cancer · 2018Trial
- The Trend of Years of Life Lost due to Gastrointestinal Cancers in Fars (Iran) 2004-2019.Iranian journal of public health · 2024Article
- Trend of hepatocellular carcinoma incidence after Bayesian correction for misclassified data in Iranian provinces.World journal of hepatology · 2017Article
- Bayesian adjustment of gastric cancer mortality rate in the presence of misclassification.World journal of gastrointestinal oncology · 2017Article
- Bayesian adjustment for over-estimation and under-estimation of gastric cancer incidence across Iranian provinces.World journal of gastrointestinal oncology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer registration is an important source for measuring the burden of cancer in a population. In practice, however, quite frequently incorrect patients are registered or data items can be inaccurately recorded or not recorded at all. Also the process or quality of these registrations varies among countries. In this paper, we briefly discussed some statistical techniques including; Mortality and Incidence Analysis Model (MIAMOD), Prevalence and Incidence Analysis Model (PIAMOD), Bayesian Inference and Capture-recapture methods, which provide tools to re-correct the incomplete or misclassified cancer statistics with regards to gastrointestinal cancers.
Indexed as
Identifiers
26744609PMC4702036What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.