Biostatistics and oncology ·
TALAPRO-3: reading a median that has not been reached
TALAPRO-3 illustrates how to interpret a median not reached, radiographic progression and uncertainty about overall survival.
Algoria · Knowledge and updates
News and guides
Updates from Algoria, bioinformatics and pharma, alongside practical biostatistics guides and Methods Lab resources.
Company · Bioinformatics · Pharma · Biostatistics
Recent news
Biostatistics and oncology ·
Anktiva: response, duration and denominators
The US expansion on 14 October raises three separate questions: who responded, how long that response lasted, and how far evidence can be carried into another population.
Biostatistics and trial design ·
Satralizumab and SatraGO: one significant trial and one non-significant trial—what can we conclude?
The regulatory announcement is an opportunity to look beyond the p value: which effect was estimated, how uncertain is it, and which assumptions would we carry into the next trial?
Pharma and biostatistics ·
ATOMIC: hazard ratio and absolute benefit at three years
The FDA approval of atezolizumab illustrates the distinction between HR, probabilities and absolute benefit. Practise with our Kaplan–Meier guide.
Practical guide ·
Kaplan–Meier, step by step
Explore censoring and numbers at risk, reproduce the same analysis in R and solve a fictional clinical case.
Algoria ·
Methods Lab: four tools to explore data and statistical methods
Effect Translator, Data Check, Survival Lab and Trial Lab are now available in Spanish and English. Explore effects, review a CSV locally and work through survival and trial simulations, with assumptions and limitations alongside each tool.
Guides and resources
Learn step by step with our guides and explore the interactive Methods Lab resources, with examples, assumptions and limitations.
Biostatistics and oncology ·
Single-arm trials: response and denominators
Audit a response proportion before interpreting it: reconstruct counts, calculate uncertainty and check what changes when unknown outcomes are excluded.
Biostatistics and trial design ·
How to plan a trial with a binary response outcome
From a clinical question to a defensible sample size: expected response rates, an important effect, power, allocation and missing outcomes.
Practical guide ·
Kaplan–Meier, step by step
Explore censoring and numbers at risk, reproduce the same analysis in R and solve a fictional clinical case.
Interactive resource
Effect Translator
Explore risks and absolute effects under the stated assumptions.
Interactive resource
Data Check
Review types, missing values and quality rules for a CSV in your browser.
Interactive resource
Survival Lab
Explore Kaplan–Meier, censoring and numbers at risk using synthetic data.
Interactive resource
Trial Lab
Compare trial scenarios with two groups and a simulated binary outcome.