Charting a lifeline
For more than a decade, a very close family member has diligently tracked his blood values during his fight with prostate cancer. The amount of prostate specific antigen (PSA) in his blood became a lifeline, something to hold onto, in times where everything else seemed uncertain. PSA values are an indication for tumor activity, and therefore: lower is better. After every new blood draw, the results were awaited with the stress that comes with hoping the PSA would be lower than the previous one.
He started noting down every single PSA measurement on a sheet of graph paper.
Next to the chart, top left, you can see written in blue ink: 'start hormonen', indicating the start of hormone therapy. This therapy proved effective for about a year, the PSA levels steadily decreasing. Early 2008 however, the PSA values started to rise. Hormone therapy was not going to be enough anymore.
And that's when the rollercoaster ride of many years of chemotherapy started.
Additional pages of graph paper were taped to the first one. Each page taped vertically, to the top, meant stressful times because of crazy high PSA levels. Each page taped horizontally, to the right, meant a lot of gratitude for having lived another year.
After ten years of living with the disease, the chart covered the whole table.
That's when I decided to digitize these manual notes, keeping it close to the original version: an annotated line graph. I wanted to do this in d3.js. The first step was to put the data into Excel.
In the final line chart, I wanted to automatically highlight line sections (using width and color) during periods where treatments took place. I also wanted to distinguish hormone therapy, chemotherapy and treatment trials. So I cleaned up the data set so that d3.js could detect these periods:
That seemed to work, specific line sections now automatically showed when certain treatments had taken place:
When I now look at this graph now, I can see what it was for me: an exercise in d3.js (in a time where I just started to learn to code using this library) and a way to deal with the data.
What also becomes very clear, is that it is no match to the original, paper version. Not even close.
The paper version breathes a personal connection, a character, dedication and an era. An era filled with deep thankfulness for every single sheet of graph paper that was taped horizontally.
About the author
Sara Maria Sprinkhuizen, PhD
I am a physicist who fell in love with MRI scanners, which launched my path into health care. After finalizing my PhD in MRI physics (Utrecht University, the Netherlands) I moved to Boston for a post-doc (Harvard Medical School, USA). I then decided to explore the medical field from a system-level perspective and joined ICHOM (Boston, USA). At ICHOM I guided working groups of physicians, patient representatives and registry leaders through the process of defining health outcomes of most importance for patients. The last years I have worked as a data analyst and visualizer, getting a close look at the daily inner workings of hospitals and the health care industry. With my health care, data analytics, and visualization experience, I provide human centered and tailor-made data support for health care organizations and scientists.