Experiments and Clinical Trials

Luis Saldarriaga

John Snow, the first epidemiologist

• In 1854, there was an outbreak of cholera in London.

• The prevailing view was that the stench arising from open sewers and rubbish piles caused the disease.

• But John Snow believed that the disease was spread from person to person through water.

Shoe leather epidemiology

• Water in London was supplied by three companies: Lambeth, Southwark and Vauxhall.

• The water was pumped from wells located in the neighborhoods.

• Snow walked the streets in order to determine in which houses cholera deaths had occurred, and which company had supplied the water.

Causes of cholera in London, 1854

• John Snow plotted on a map the location of all the cases he learned of.

• He established that the areas supplied by Southwark and Vauxhall, which took water from the Thames, downstream from London, had a high cholera death rate (map 1). That water was contaminated with sewerage.

• In contrast, the areas supplied by Lambeth, which took water from upstream, had lower death rates.

Only those residing in the purple shaded region were affected by cholera.

Deaths and death rates from cholera in households supplied by the Southwark and

Vauxhall Water Company and by the Lambeth Water Company (London, 1854)

Houses Cholera deaths

Deaths per 10.000 houses

Southwark and Vauxhall

40.046 1.263 315 (3.15%)

Lambeth Company

26.107 98 37 (0.37%)

Rest of London

256.423 1.422 59 (0.59%)

Causes of cholera in London, 1854

• Later, Snow found a close association between the density of cholera cases in his own neighborhood and a single well located on Broad Street.

• This convinced the municipal authorities to remove the pump handle of the Broad Street well, which probably prevented a second outbreak.

The water pump on Broad Street

The research process

• Select a field and a topic for research.

• Plan the research and write up the plan as a research protocol.

• Describe and analyze the research results.

• The research results then need to be carefully and objectively interpreted.

• Research is not complete until it is communicated (publish or perish).

The sample size

• A crucial question when planning the research is the type and size of sample to be studied. This is because the entire population cannot be studied.

• The sample size appropriate to provide the answer to the research question has to be defined.

• If the sample size is too small, the study will not provide definitive answers.

The protocol

• After developing the plan for the research, it has to be written down as a protocol. It starts with a title and a summary.

• The project description should include the rationale for the study, objective, methodology, ethical considerations and gender issues (if relevant).

The protocol

• The project description should also include the statistical methods used for sample size calculation and for data management and analysis.

• And the protocol should include a small number of recent and relevant references to previous work on the topic.

Data analysis

• Descriptive statistics are useful to summarize and present the data.

• Tools of descriptive statistics include tabulation, calculations, graphs, and correlation.

• Tabulations include frequency distribution tables, and cross tabulations.

• Data can be visually displayed in graphs.

Data analysis

• Calculations estimate the central tendency in numerical data (the mean, median and mode), the variability (range, standard deviation and percentiles), as well as ratios and rates.

• The frequency distribution curve is particularly important to show how the data are distributed, with implications for subsequent statistical analysis.

The null hypothesis

• A research must not be carried out to prove a hypothesis, but only to test it.

• The null hypothesis is the assumption that the research hypothesis is not true.

• If the results do not support the null hypothesis, then the research hypothesis is more likely to be true. But usually there is no absolute certainty about the validity of scientific results, only a high level of probability.

The p value

• The p value is the probability that the null hypothesis is true.

• If p is less than 1 in 20 (p < 0.05), most researchers consider that the null hypothesis is disproved.

• In cases like this, the observed difference is taken as significant.

The p value

• But significance is not proof. In fact, hypotheses can never be proven to be absolutely true.

• The most we can say is that there is a high probability that the hypothesis provides a valid explanation of the phenomenon being studied.

What is “statistical significance?”

• The term “statistical significance” simply means that the finding or difference is unlikely to be due to chance. The association of two variables should not imply a cause-and-effect relationship.

• Confounding factors and bias, whether in selection or measurement, must be excluded before jumping into any conclusion.

Establishing a cause-effect relationship

One can infer that one phenomenon causes the other if it fulfils five criteria:

• Statistical significance (p < 0.05).

• Consistency (you get similar results when repeating the experiments).

• A graded response to a graded dose.

• A temporal relationship.

• A plausible mechanism.

“Publish or perish”

• Research is not complete until its results are published in scientific journals.

• But a scientific report will not be accepted for publication until it has been approved by other scientists, who serve as referees (peer review).

• Another way to inform the scientific community is to present the results in scientific meetings.

The research article

• Introduction: why this research was done.

• Methods: how this research was done.

• Results: what the researchers got.

• Discussion: implications of this research for its field. Why the findings are relevant.

• References: about what has been done before.

• Abstract: a brief summary of the present research.

Moves in Introductions

• MOVE 1: What the topic is. Why it is important.

• MOVE 2: The nature of a problem, its significance. What has been done.

• MOVE 3: The gap, a very specific part of the problem or conflicting data, which brought about the need for the research.

• MOVE 4: Filling the gap (solving the specific part of the problem). Main and secondary objectives of the report.