Product Images Anastrozole
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 8 images provide visual information about the product associated with Anastrozole NDC 59651-236 by Aurobindo Pharma Limited, such as packaging, labeling, and the appearance of the drug itself. This resource could be helpful for medical professionals, pharmacists, and patients seeking to verify medication information and ensure they have the correct product.
This appears to be a graph displaying "Disease-free survival in months" based on the number of patients at risk who were given either "anastrozole" or "tamoxifen". The numbers listed may refer to the amount of patients at risk at specific time intervals.*
This appears to be a graph showing the results of a clinical trial comparing the effectiveness of two treatments (anastrozole and tamoxifen) for an undisclosed condition over a period of time (measured in months). The x-axis shows the time elapsed, while the y-axis shows the percentage of patients who have not experienced the event (disease progression or death). The graph is a Kaplan-Meier curve and has been truncated on the y-axis for clarity. There is also a table below the graph showing the number of patients at risk for each treatment at certain time points.*
This appears to be a table or graph displaying data related to an experimental treatment using a drug called Anastrolzole and a comparison with a drug called Tamoxifen. The data includes the time to event in months and the number of patients at risk. There is also a note at the bottom indicating that the vertical axis has been truncated for clarity.*
The text appears to be a medical graph showing the progression of a certain condition over time with two randomized treatments, anastrozole and tamoxifen. The x-axis shows time in months while the y-axis shows the proportion of the condition not progressing. The data points are marked along the graph with corresponding percentages and at-risk numbers.*
* The product label images have been analyzed using a combination of traditional computing and machine learning techniques. It should be noted that the descriptions provided may not be entirely accurate as they are experimental in nature. Use the information in this page at your own discretion and risk.