Biostatistics and Clinical SAS Programming

Statistical analysis plays a pivotal role in allowing clinical research professionals to draw rational and accurate inferences from the data collection and also contributes to make decisions. The statistical inputs in a protocol design helps to provide formal accounting for sources of variability in study subjects response to the treatment drug. Statistical inputs are characterized by launching an objective outline for conducting an investigation. The statistical programmers provide the theoretical data for upholding the scientific background. The programmers also support in designing the data production through experimentation and emphasis on the quantification corresponding to influence of the probability. The expert programmers also provide data solutions to estimate the systematic and random effects and add value to analyze the theoretical data using formal methods. The statistical inputs also involve information on defining the patient population, randomization and stratification with industry standard practices.

The primary end point and secondary end points correspond to the objective of the clinical trial in progress. It is cognizant that both primary and secondary end points can be made up of several end points called a ‘family of end points’. Each of these end points play a vital role in ensuring the successive progression of the study towards the study objective. The trial end points can be continuous, binary or time to event end points. The statistical programmers bring their expertise in analyzing the data points using HAM-D symptom rating scale for a composite endpoint with multi component end points. We also expertise in implementing statistical methods like single-step and multi-step procedures such as Bonferroni method, Holm procedure, Hochberg procedure, Prospective Alpha Allocation Scheme, The Fixed- Sequence Method, The Fall back method and Gate Keeping strategies.

Sample size is a part of the population that has been chosen in a clinical trial. The standard deviation of a sample can be used to approximate the standard deviation of a population. It is important to determine the optimal sample size for a clinical study assures an adequate influence to detect statistical significance. The calculation of an appropriate sample size is mainly influenced by certain factors like P value, Power, Effect, Alternative hypothesis. The study design has a major impact on the sample size. Experimental studies need lesser sample while the descriptive studies need hundreds of subject to give acceptable assurance interval for minor effects. The statisticians bring immaculate experience in analyzing the alpha level, standard deviation, minimum detectable difference, Power and withdrawals.

Randomization plan is a critical feature in a clinical study design to control on the bias. Randomization plan design is set up in a such way that there is equality and no bias in the assignment of the treatment drug at each investigator’s site. It is also the process of assigning patients by chance to the groups that receive different treatments. In a modest clinical trial design, the investigational group receives the treatment drug and the control group receives the standard therapy. At the end of each of the study the clinical researchers compare both the groups to measure the effectiveness of the treatment. The randomization plan works on the principle of simple randomization, block randomization, stratified randomization and covariate adaptive randomization. The expert team perform the analysis according to intent –to- treat (ITT) and per protocol principle. The team has proficiency in also adapting to customized tools to prepare the randomization plan.

A case report form (CRF) is a specialized document in clinical trial. The principle of the case report form is protocol driven, robust in content and should be enabled to collect study specific data. It can be paper based CRF forms and also electronic CRF. The idea of the CRF from is to facilitate the collection of accurate data and reporting. It is imperative to have a strong collaboration between the statistical programmer and other key stakeholders which has a huge impact on the accurate designing of the CRF in a clinical study. The CRF is a link between the protocol, the database and statistical analysis plan. The expert trial statisticians and programmers provide their support in analysis by generating the collected data. Our trial statistician and trial programmers are heavily involved during the CRF finalization by providing their valuable inputs.

The statistical analysis plan is a comprehensive document that contains a detailed technical description of the principal features of the analysis outlined in the protocol. It also includes wide-ranging procedures for executing the statistical analysis of the primary and secondary variables and other data. Although the Statistical analysis plan is an objective document, the document shall be reviewed in conjunction with the protocol. It is one of the crucial regulatory confidential document in the development of a clinical trial. The key aspects to be considered during the development of the statistical analysis plan are data monitoring, interim statistical analysis, integrated statistical analysis plan and statistical analysis plan for the clinical study. The statistical methodology includes data points like hypothesis of the clinical study , primary and secondary end points, develop a strategy to reduce the bias, sample size collection and to define statistical methods for the clinical trial analysis.

Statistical programming helps in outlining the study end points, sample size calculation, interim analysis planning and hypothesis of testing procedures. The statistical analysis helps to uphold the integrity of a clinical trial. Biostatisticians are involved in every step of the clinical research including clinical trial design, protocol development, data management and monitoring, data analysis. The role of the statistical programmers is to use their superior technical and programming skills to allow the clinical trial statisticians to perform the statistical analysis more efficiently. SAS experts provide market needed competitive edge from remodeling trial designs to delivering leading platforms for data transparency. They work on data sets to meet the study requirements as per the regulatory authority guidelines.

As an integral part of the regulatory reporting requirements, it is imperative to generate tables, graphs and listings for reporting purpose. The clinical trial data is thoroughly analyzed by expert team members and presented as tables, graphs and listings in clinical trial reports. They play a unique role since it acts as a one stop destination to understand and analyze any queries from regulatory authorities. The listings basically have all the information that one needs to know involved in a clinical trial. The significance of SAS in the pharma programming arena by producing tables, graphs and listings by mock annotations. The derived data sets through SAS is used as a base to write the code to produce tables and listings. The step wise process followed by SAS team experts work on the protocol and CRF, statistical analysis plan, mock databases, annotated CRF, annotated mocks, derived datasets, programming rules which leads to the generation of perfect tables and listings that are required for further analysis at any stage of the life cycle of the study drug.

The statistical reports provide an overview to the complete clinical trial process. This report describes statistical methods with accurate details to access the source data to verify the reported results. It also enables to quantify the findings and present them with appropriate indicators to measure the errors. The statistical reports also emphasis on the blinding observations and provide detailed analysis of the treatment complication in the trial subjects. The statistical reports also highlight on the statistical measures and methods followed during the process of the clinical trial. The experienced biostatistician provides substantial help in preparation and analyzing the reports for further interpretation of the safety and efficacy of the trial drug. The statistical reports also focus on the actual outcomes such as means and standard deviations at derived intervals.