ODF4, MAGEA3, and MAGEB4: potential biomarkers in patients with transitional cell carcinoma

Background: This study aimed to evaluate the diagnostic value of outer dense fiber 4 [ODF4], melanoma associated antigen A3 [MAGEA3], and MAGEAB4 mRNAs in transitional cell carcinoma [TCC], using a small amount of cell reverse transcriptase-polymerase chain reaction [RT-PCR] on urinary exfoliated cells

Methods: We recruited a total of 105 suspected TCC patients and 54 sex- and age-matched non-TCC controls. The candidates' genetic expression patterns were investigated with RT-PCR, while reverse transcription quantitative PCR was applied to quantify and compare each mRNA level between cases and control groups

Results: The sensitivity of ODF4, MAGEA3, and MAGEAB4 RT-PCR was 54.8%, 63%, and 53.4%, whereas the specificity was 73.7%, 86%, and 94.7%, respectively. Combining ODF4, MAGEA3, and MAGEAB4 RT-PCR offered a relatively higher sensitivity [83.6%]

Conclusion: RT-PCR with ODF4, MAGEA3, and MAGEAB4 on urinary exfoliated cells could provide clinicians with a promising method to improve TCC diagnosis, especially in the case of gross hematuria and catheterization. The method used here is non-invasive, simple and convenient, and unlike cytology, it does not rely directly on expert professional opinions. These features can be of particular importance to the management of TCC patients in whom regular and lifelong surveillance is required

Systematic review of priority setting studies in health research in the Islamic Republic of Iran

Background: Several research priority-setting studies have been conducted in different countries, including the Islamic Republic of Iran.

Aims: We conducted a systematic review and evaluated the quality of the priority-setting reports about health research in the Islamic Republic of Iran.

Methods: English and Farsi databases were searched from January to July 2016 to extract reports [up to December 2015] about priority setting in health research in the Islamic Republic of Iran. We constructed a checklist to extract data from the identified studies. Articles were studied in detail and content analysis was carried out. Relevant items were scored and analysed using Microsoft Excel.

Results: We identified 36 articles. Eight articles involved all the main stakeholders. About half the articles used valid criteria for ranking. Transparency was fulfilled in 13 articles. Upstream rules and regulations were ignored in 26 articles. An implementation plan was considered in 9 articles and context analysis was demonstrated in only 3.

Conclusions: Developing standard packages for priority setting, training of researchers and improving the capacity of organizations may improve the quality of priority-setting studies in the future.

application of network scale up method on estimating the prevalence of some disabilities in the southeast of Iran

More than a billion people have some form of disabilities worldwide. Persons living with a disability have many needs [including physically, mentally, and socially needs]. Estimating the size of disabled population is a challenge in health systems. An innovative indirect method to estimate the size of populations is network scale up [NSU] having widely used for hidden populations. The method is based-on the social network of individuals. We assessed the capability of NSU to estimate persons living with a disability being a middle population [neither non-hidden nor hidden populations] in the Southeast of Iran [Kerman City, southeast Iran]. A total of 3052 of Kermanian people over 20 year old were interviewed by simple random sampling. We asked them whether they knew acquaintances with complete blindness, severe visual impairment, deafness, severe hearing impairment, limb defects, and mental retardation, if yes; we wanted them to count them. Based on the network scale up method, the prevalence of the populations was estimated at 5.21/1000 in Kerman City where severe visual impairment was 1.35, mental retardation was 1.039, severe hearing impairment was 1.005, limb defects was 0.78, deafness was 0.59, and complete blindness was 0.56 [per 1000 inhabitants]. The results were not exactly comparable to previous studies using different methods such as surveys. Although the method has some limitations, considering its easiness and cost-effectiveness, modified NSU could be used when direct methods are not practicable