Tips & Tricks
The abstract submission is open from October 31st 2016 till Februari 3rd 2017.
The most important function of your abstract is to show that you have a valuable contribution to the congress and secondly, to lure the audience to your presentation. Abstracts will only be taken into account for the abstract selection procedure when they are written in English and do not exceed a maximum of 350 words. Furthermore, unfortunately, we cannot accept case-studies, reviews and literature studies (except for meta-analysis).
* Note: Preliminary results are allowed in your abstract.
Abstracts should contain the following subheadings:
There are no strict rules for writing an abstract, although these guidelines might help you take your abstract to the next level. Before considering these guidelines, keep in mind that the maximum number of words is 350.
How long should my abstract be?
The limit is 350 words. The key is to state the important aspects in your abstract as brief as possible. Be sure it remains understandable.
How much background information should I assume my audience has?
Although it is important to know who your audience is, in general, it is best to assume little knowledge. This often requires simplifying your abstract to some extent. Be careful that you do not alter the facts in your abstract in the process of making it accessible to others.
Which parts of an abstract are especially important?
The two most important parts of an abstract are the title and the conclusions. These are important because they are often the only chance to interest people in your study and to clarify what your abstract is about.
How do I create a proper title?
Make it short and clear. Formulate a clear research question and, if possible, what the major result was. Make the title interesting in order for people to continue reading. Consider these three titles for the same study:
Treatment of eczema in children.
Probiotics in the treatment of eczema in childhood: a randomized controlled trial.
No effect of probiotics in the treatment of childhood eczema: a randomized controlled trial.
The first is too general and therefore uninformative. The second is much more informative than the first, but the third is the best because it gives the outcome away to the reader.
What is important in the conclusion?
The conclusion should not only state your findings, but also what this implies. Remember that most readers will, if your title has peaked their interest, read the conclusion next. Be careful not to conclude more than your results allow, but do state what your results imply.
State in the introduction clearly how the study contributes to society. Give background information why this study was done. It is of great importance to clearly state the aim of your study. Be specific. Once your researchquestion is clear to the reader, the rest of the abstract is easier to understand.
In the methods, make sure the comparisons between variables are explained. In the results, avoid hanging comparisons:
BAD: children treated with probiotics had lower eczema scores at the end of the study
The reader will ask: lower than who or what?
GOOD: children treated with probiotics had lower eczema scores at the end of the study than those treated with placebo.
Find someone to read your abstract whose unfamiliar with your work. It will help you identify confusing passages for which you have become “blind”. And last but not least, check your abstract for grammatical errors and misspelling.
This is where you mention the statistical methods you applied and which software was used.
Section “Results”: inferential statistics
Confidence intervals are more informative than P-values. For example: the difference between the mean blood pressures of the groups is significant (P < 0.05) with the 95% confidence interval for the difference between the mean blood pressure of group 1 and the mean blood pressure of group 2 ranges from 3.14 mm Hg to 8.68 mm Hg. Be concise in the description of preliminary activities, like checking assumptions. Give the results of all relevant statistical tests you performed. Be sure to answer your main research question(s). Give estimates, and standard errors of these estimates, of the coefficients in your final regression model(s), if any. Give the interpretation of the coefficient(s) of the most relevant explanatory variable(s) in words.Section “Conclusions / Discussion”
Repeat the main result(s) from the Results section without the statistical details. Give a brief answer to your research question. Do not present any numbers that were not mentioned in the results section.
To give you an idea of a well written abstract, please take a look at this abstract, written by former ISCOMS-participant Janet Vos:
Author: Janet Vos
Proven non-carriers in BRCA families have an earlier age of onset of breast cancer
Field of research
It is assumed that women who test negative for their family-specific BRCA1/2 mutation are not at increased risk anymore to develop breast or ovarian cancer. In the Netherlands, they are thus dismissed from intensive breast cancer screening and referred to the national breast cancer screening program starting at age 50. However, risk estimates for proven non-carriers in BRCA mutation families are inconsistent for breast cancer and are lacking for ovarian cancer. We aimed to assess the age-related risks for breast and ovarian cancer for proven non-carriers in these families.
Materials & Methods
A consecutive cohort study ascertained 464 proven non-carriers who had at least one first-degree relative with a pathogenic BRCA mutation. Kaplan-Meier analyses were used to estimate the age-related cancer risks, and we calculated standardized incidence ratios.
In the 464 non-carriers, 17 breast cancers were detected at a mean age of 47 years (95%CI 32-61) and two ovarian cancers were found at the age of 43 and 55 years. By age 50, the breast cancer risk among non-carriers was 6.4% (95%CI 2.9-9.8%) and the ovarian cancer risk was 0.4% (95%CI 0-1.3%). At this age the breast cancer risk in non-carriers was significantly higher than the risk in the general population. In particular, the number of breast cancers among proven non-carriers in BRCA1 families was higher than expected for the general population (SIR 40-49yr: BRCA1 4.5 (95%CI 1.8-9.2), BRCA2 2.1 (95%CI 0.3-7.6)). In the BRCA1 cohort, the mean number of breast cancer cases was higher in families in which non-carriers were diagnosed before age 50 (p=0.04).
The age at diagnosis of breast cancer in non-carriers in BRCA mutation families is younger than expected, yielding an increased risk in the fifth decade. This effect is most evident in BRCA1 families. If our results are confirmed by others, this could affect the advice given on breast cancer screening to proven non-carriers between age 40 and 50 in BRCA positive families.
BRCA, non-carrier, breast cancer, risk
The abstract submission is now closed.