Randomized controlled trials often suffer from two major complications, i.e., noncompliance and missing outcomes. One potential solution to this problem is a statistical concept called intention-to-treat (ITT) analysis. ITT analysis includes every subject who is randomized according to randomized treatment assignment. It ignores noncompliance, protocol deviations, withdrawal, and anything that happens after randomization. ITT analysis maintains prognostic balance generated from the original random treatment allocation. In ITT analysis, estimate of treatment effect is generally conservative. A better application of the ITT approach is possible if complete outcome data are available for all randomized subjects. Per-protocol population is defined as a subset of the ITT population who completed the study without any major protocol violations.

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Now-a-days there is significant discussion about patient-reported outcomes (PRO) in medical world. The following article covers almost all the areas of PRO including-their importance, important concepts for understanding of PRO, significance, ideal properties, types, development and evaluation of PRO instruments. It is useful for physicians, pharmacists and patients for the assessment and improvement of the therapy.

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MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression in diverse biological process. They act as intracellular mediators that are necessary for various biological processes. MicroRNAs targeting pathways of human disease provide a new and potential powerful candidate for therapeutic intervention against various pathological conditions. Even though, the information about miRNA biology has significantly enriched but we still do not completely understand the mechanism of miRNA gene regulation. Various groups across the globe and pharmaceutical companies are conducting research and developments to explore miRNA based therapy and build a whole new area of miroRNA therapeutics. Consequently, few miRNAs have entered the preclinical and clinical stage and soon might be available in the market for use in humans.

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Agreement between measurements refers to the degree of concordance between two (or more) sets of measurements. Statistical methods to test agreement are used to assess inter-rater variability or to decide whether one technique for measuring a variable can substitute another. In this article, we look at statistical measures of agreement for different types of data and discuss the differences between these and those for assessing correlation.

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The elderly population is a large and the fastest-growing portion of the population worldwide. The elderly make up the lion's share of patients for certain health conditions including cancer, cardiovascular disease, arthritis, and Parkinson's disease, among others in most parts of the world. Furthermore, elderly make up the majority of patients for many medications treating chronic conditions. Typically, clinical trials conducted in adult population include patients between the ages of 18 and 64 years. However, drugs should be studied in all age groups and trial participants should be representative of the patient population receiving the therapy in daily medical practice. Elderly patients are poorly represented in clinical trials. Hence, there is inadequate evidence and knowledge about responses of geriatric patients to medications. Regulatory authorities in developed countries urge to avoid arbitrary upper age limits and advise researchers and industry not to exclude elderly people from clinical trials without a valid reason. Since last few years Indian regulatory authority has been stipulating upper age limit for studies conducted in India. The Central Drugs Standard Control Organization (CDSCO) will be doing a great contribution to the researchers if it changes its view on stipulating upper age restrictions in clinical studies. This article describes the need for including elderly patients in the clinical trials in order to garner data from geriatric patients who form major medication users in most of the chronic diseases.

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During the conduct of clinical trials, it is not uncommon to have protocol violations or inability to assess outcomes. This article in our series on common pitfalls in statistical analysis explains the complexities of analyzing results from such trials and highlights the importance of "intention-to-treat" analysis.

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In clinical research, study results, which are statistically significant are often interpreted as being clinically important. While statistical significance indicates the reliability of the study results, clinical significance reflects its impact on clinical practice. The third article in this series exploring pitfalls in statistical analysis clarifies the importance of differentiating between statistical significance and clinical significance.

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Statistics plays a vital role in biomedical research. It helps present data precisely and draws the meaningful conclusions. While presenting data, one should be aware of using adequate statistical measures. In biomedical journals, Standard Error of Mean (SEM) and Standard Deviation (SD) are used interchangeably to express the variability; though they measure different parameters. SEM quantifies uncertainty in estimate of the mean whereas SD indicates dispersion of the data from mean. As readers are generally interested in knowing the variability within sample, descriptive data should be precisely summarized with SD. Use of SEM should be limited to compute CI which measures the precision of population estimate. Journals can avoid such errors by requiring authors to adhere to their guidelines.

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Many clinical trials involve following patients for a long time. The primary event of interest in those studies is death, relapse, adverse drug reaction or development of a new disease. The follow-up time for the study may range from few weeks to many years. A different set of statistical procedures are employed to analyze the data, which involves time to event an analysis. It is a very useful tool in clinical research and provides invaluable information about an intervention. This article introduces the researcher to the different tools of survival analysis.

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In biomedical research, we are often interested in quantifying the relationship between an exposure and an outcome. “Odds” and “Risk” are the most common terms which are used as measures of association between variables. In this article, which is the fourth in the series of common pitfalls in statistical analysis, we explain the meaning of risk and odds and the difference between the two.

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Background: Successful recruitment of patients is known to be one of the most challenging aspects in conduct of randomized controlled trials. Inadequate patient retention during conduct of trial affects conclusive results. Objective: To assess the level of challenges faced by Indian investigators in recruitment and retention of trial subjects. Methods: We developed a survey questionnaire on challenges encountered by investigators in subject recruitment and retention which was hosted on a web portal. Results: Seventy-three investigators from India participated in the survey. The frequently encountered challenges in subject recruitment were complexity of study protocol (38%), lack of awareness about clinical trials in patients (37%), and sociocultural issues related to trial participation (37%). About 63% of participants strongly agreed that creating a positive awareness about clinical trials among people through press and media, having a dedicated clinical research coordinator for trial (50.7%), and designing a recruitment strategy prior to study initiation (46.6%) would enhance recruitment. Almost 50.7% of participants agreed that interacting with medical community in vicinity of the study site and educating patients about clinical trials during routine outpatient department visits (46.6%) would enhance recruitment. Experiencing a serious adverse event, subject's fear for study procedures (47%) and side effects (44%) were thought to have a moderate effect on subject retention. Conclusion: Our survey has put forth factors related to negative publicity by media, lack of patient education about clinical trials; complex study designs are barriers to clinical trial recruitment in India. It is essential to devise innovative and effective strategies focusing on education of public and mass media about clinical research in India.

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Multiple testing refers to situations where a dataset is subjected to statistical testing multiple times - either at multiple time-points or through multiple subgroups or for multiple end-points. This amplifies the probability of a false-positive finding. In this article, we look at the consequences of multiple testing and explore various methods to deal with this issue.

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Correlation is a statistical technique which shows whether and how strongly two continuous variables are related. In this article, which is the eighth part in a series on 'Common pitfalls in Statistical Analysis', we look at the interpretation of the correlation coefficient and examine various situations in which the use of technique of correlation may be inappropriate.

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Electronic health record (EHR) is increasingly being implemented in many developing countries. It is the need of the hour because it improves the quality of health care and is also cost-effective. Technologies can introduce some hazards hence safety of information in the system is a real challenge. Recent news of security breaches has put a question mark on this system. Despite its increased usefulness, and increasing enthusiasm in its adoption, not much attention is being paid to the ethical issues that might arise. Securing EHR with an encrypted password is a probable option. The purpose of this article is to discuss the various ethical issues arising in the use of the EHRs and their possible solutions.

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Background and Objectives: Self medication is an important concern for health authorities at global level. This study was aimed to find the prevalence of self medication for allopathic drugs and associated factors among households of urban community. This study was also aimed at assessing the attitude of respondents who had experienced self-medication. Materials and Methods: This cross-sectional study was done in field practice area attached to a medical institution in urban Puducherry. A total of 352 subjects from 124 households were selected by random sampling. With pretested interview schedule, information regarding self-medication use in the past three months and associated sociodemographic factors, purpose, source of drug procurement, attitude toward self-medication use were collected. Results: Prevalence of self-medication was found to be 11.9%. Males, age >40 years and involving in moderate level activity of occupation, were found to be significantly associated with higher self-medication usage (P < 0.05). Fever (31%), headache (19%), and abdominal pain (16.7%) are most common illnesses where self-medication is being used. Telling the symptoms to pharmacist (38.1%) was the commonest method adopted to procure drugs by the users. Majority of the self-medication users expressed that self-medication is harmless (66.6%) and they are going to use (90%) and advice others also (73.8%) to use self-medication drugs. Conclusion: Self-medication is an important health issue in this area. Health education of the public and regulation of pharmacies may help in limiting the self-medication practices.

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Objective: The primary objective of this study was to evaluate the knowledge, attitude, and practices (KAP) of the healthcare professionals about pharmacovigilance in Dhanalakshmi Srinivasan Medical College and Hospital (DSMCH), Perambalur (Tamil Nadu), a tertiary care teaching hospital. The second primary objective was to assess the causation of underreporting of adverse drug reactions (ADRs) as it needs to be well-assessed in India. The secondary objective was to compare the findings of this study with the results of the published studies from India on evaluation of the KAP of pharmacovigilance among healthcare professional. Materials and Methods: A cross-sectional study was carried out using a pretested questionnaire. The questionnaire was designed to assess the KAP regarding pharmacovigilance. The healthcare professionals (doctors, nurses, and pharmacists) working in the DSMCH, Perambalur (Tamil Nadu) during the study period were included. Only those who gave their consent to participate were included in the study. The data was analyzed by using the Statistical Package for Social Sciences (SPSS) statistical software, version 16. Results: One hundred and fifty pretested questionnaires were distributed among the healthcare professionals and 101 responded. 62.4% healthcare workers gave correct response regarding the definition of pharmacovigilance. 75.2% of healthcare workers were aware regarding the existence of a National Pharmacovigilance Program of India. 69.3% healthcare professional agreed that ADR reporting is a professional obligation for them. Among the participants, 64.4% have experienced ADRs in patients, but only 22.8% have ever reported ADR to pharmacovigilance center. Unfortunately only 53.5% healthcare workers have been trained for reporting adverse reactions. But, 97% healthcare professionals agreed that reporting of ADR is necessary and 92.1% were of the view that pharmacovigilance should be taught in detail to healthcare professional. Conclusion: This study demonstrated that knowledge and attitude towards pharmacovigilance is gradually improving among healthcare professionals, but unfortunately the actual practice of ADR reporting is still deficient among them.

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Objectives: Spontaneous reporting is an important tool in pharmacovigilance. However, its success depends on cooperative and motivated prescribers. Under-reporting of adverse drug reactions (ADRs) by prescribers is a common problem. The present study was undertaken to evaluate the knowledge, attitude, and practices (KAP) regarding ADR reporting among prescribers at the Civil Hospital, Ahmedabad, to get an insight into the causes of under-reporting of ADRs. Materials and Methods: A pretested KAP questionnaire comprising of 15 questions (knowledge 6, attitude 5, and practice 4) was administered to 436 prescribers. The questionnaires were assessed for their completeness (maximum score 20) and the type of responses regarding ADR reporting. Microsoft Excel worksheet (Microsoft Office 2007) and Chi-Square test were used for statistical analysis. Results: A total of 260 (61%) prescribers completed the questionnaire (mean score of completion 18.04). The response rate of resident doctors (70.7%) was better than consultants (34.5%) (P < 0.001). ADR reporting was considered important by 97.3% of the respondents; primarily for improving patient safety (28.8%) and identifying new ADRs (24.6%). A majority of the respondents opined that they would like to report serious ADRs (56%). However, only 15% of the prescribers had reported ADRs previously. The reasons cited for this were lack of information on where (70%) and how (68%) to report and the lack of access to reporting forms (49.2%). Preferred methods for reporting were e-mail (56%) and personal communication (42%). Conclusion: The prescribers are aware of the ADRs and the importance of their reporting. However, under reporting and lack of knowledge about the reporting system are clearly evident. Creating awareness about ADR reporting and devising means to make it easy and convenient may aid in improving spontaneous reporting.

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Real world evidence is important as it complements data from randomised controlled trials (RCTs). Both have limitations in design, interpretation, and extrapolatability. It is imperative one designs real world studies in the right way, else it can be misleading. An RCT is always considered higher in the evidence ladder and when there is discordance between a real world study and an RCT, it is the latter which is always considered pristine because of the way it is conducted, e.g., randomization, prospective, double-blind, etc. A real world study can also be done prospectively, and propensity score matching can be used to construct comparable cohorts but may not be able to account for certain biases or confounding factors the way an RCT can do. Nevertheless, comparative effectiveness research in the real world is being resorted to, especially for efficiency studies or pharmacoeconomic analyses, and with the advent of machine learning, the electronic healthcare database mining can result in algorithms that help doctors identify clinical characteristics that correlate with optimal response of a patient to a drug/regimen, thus helping him/her select the right patient for the right drug.

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Plagiarism is the wrongful presentation of somebody else's work or idea as one's own without adequately attributing it to the source. Most authors know that plagiarism is an unethical publication practice. Yet, it is a serious problem in the medical writing arena. Plagiarism is perhaps the commonest ethical issue plaguing medical writing. In this article, we highlight the different types of plagiarism and address the issues of plagiarism of text, plagiarism of ideas, mosaic plagiarism, self-plagiarism, and duplicate publication. An act of plagiarism can have several repercussions for the author, the journal in question and the publication house as a whole. Sometimes, strict disciplinary action is also taken against the plagiarist. The article cites examples of retraction of articles, suspension of authors, apology letters from journal editors, and other such actions against plagiarism.

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In this article in our series on common pitfalls in statistical analysis, we look at some of the attributes of diagnostic tests (i.e., tests which are used to determine whether an individual does or does not have disease). The next article in this series will focus on further issues related to diagnostic tests.

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The use of stem cells as medicines is a promising and upcoming area of research as they may be able to help the body to regenerate damaged or lost tissue in a host of diseases like Parkinson's, multiple sclerosis, heart disease, liver disease, spinal cord damage, cancer and many more. Translating basic stem cell research into routine therapies is a complex multi-step process which entails the challenge related to managing the expected therapeutic benefits with the potential risks while complying with the existing regulations and guidelines. While in the United States (US) and European Union (EU) regulations are in place, in India, we do not have a well-defined regulatory framework for "stem cell based products (SCBP)". There are several areas that need to be addressed as it is quite different from that of pharmaceuticals. These range from establishing batch consistency, product stability to product safety and efficacy through pre-clinical, clinical studies and marketing authorization. This review summarizes the existing regulations/guidelines in US, EU, India, and the associated challenges in developing SCBP with emphasis on clinical aspects.

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