You may have heard the saying—popularized but not coined by Mark Twain—“There are three type of lies: lies, damn lies and statistics.” People often bring it up to make the point that citing statistics is an inherently shady business, easily manipulated by bad actors for nefarious purposes. Indeed, that probably was the phrase’s original intent. Twain credits it to Benjamin Disraeli, a former UK prime minister, and it does sound like the words of a jaded politician. Interestingly, even though people point to it as an example of Twain’s wry cynicism, his own use of the quote was more self-deprecating. 

In his autobiography, Twain noted that in his youth he could write 3,000 words a day, but in old age his output had dropped to about half. At first, he was harshly self-critical over this decline but, upon reflection, he realized he had lately been spending only half as much time writing, so in fact his output was consistent throughout his life after all. 

“Figures often beguile me, particularly when I have the arranging of them myself,” Twain admits in his autobiography before using the Disraeli quote to chastise himself. When he had a full accounting of his productivity, his opinion changed. What he needed was a relative measure rather than an absolute one. In other words, he needed context. 

To teach ODs to be more astute consumers of medical statistics—to find that all-important context—this month we’re beginning a four-part series on scientific research and how it relates to clinical practice. As optometry is now the dominant provider of primary eye care in America, practitioners need to know the scientific underpinnings of their actions more than previous generations might have. When the work of optometry was predominantly refraction and dispensing, knowing the latest research was less vital day to day. The principles of visual optics haven’t changed in centuries, but primary care brings optometry into the ever-changing world of evidence-based medicine—avidly for some, kicking and screaming for others. Either way, its importance will only continue to rise.

Review of Optometry has been devoted to describing clinical insights gleaned from the very latest medical research for years now. Our online news feed provides well over 700 journal article summaries every year. I can say without (much) bragging that there’s simply no comparable outlet anywhere else for the latest medical research as it relates to optometry. In addition to summarizing a study’s key points, our news stories will now link to the abstracts themselves so that interested ODs can go deeper if they want.

To help, this new series will teach you look at statistics more clearly, starting with the building blocks. The terminology of research is often baffling. If your eyes glaze over at the thought of p-values and ROC curves and hazard ratios and the like, not to worry. In this feature from this month's issue, Andrew Pucker, OD, explains them in clear and simple ways in part one of this series. Future installments will give you the tools to read a study skeptically, evaluate the landmark clinical trials in eye care and understand the inner workings of study design and analysis.

Statistics can be misinterpreted even when there’s no bad intent; lack of familiarity combined with reverence for peer-reviewed literature is enough to “beguile,” as Twain said. But, when armed with the right tools, you’ll be able to learn from others while thinking for yourself.