43 - Global Author Collaboration in Neonatal Randomized Clinical Trials

Publication Number: 4042.43

Emily Rodriguez, Boston Children's Hospital, Boston, MA, United States; John Zupancic, Harvard Medical School, Boston, MA, United States; Sarah Morton, Boston Children's Hospital, Boston, MA, United States; Susanne Hay, Harvard Medical School, Boston, MA, United States; Brian King, Harvard Medical School, Boston, MA, United States; Maria Laura Mourão, Beth Israel Deaconess Medical Center, Boston, MA, United States; Sarah Kunz, Harvard Medical School, Boston, MA, United States

Background: Low income and lower-middle income countries are disproportionately burdened by neonatal morbidity and mortality. Randomized clinical trials (RCTs) in neonatology are designed to determine best practices that can be disseminated and implemented in order to improve neonatal outcomes. While it is important to ensure that clinical trials in neonatology are being performed in settings with the greatest needs, it is also critical to ensure that authorship includes individuals from the countries in which studies take place.

Objective: To quantitatively assess global representation in the neonatal clinical trial literature by country of author's institution and setting in which trials are conducted.

Design/Methods: This was a retrospective analysis using all clinical trials from 2002-2022 within the NeoCanon database, a validated database of all neonatal RCTs published over this time period. We extracted the country of the first author's (FA) affiliated institution(s) and the country in which each trial was performed (study setting; SS). Income level of each country was designated according to the World Bank classification low, lower-middle, upper-middle, and high income. For each year, the total number of FAs affiliated with each country, as well as the number of studies performed in each country, were calculated. FA affiliations and SSs were then tallied by country income level. The data were converted to an adjacency matrix to facilitate network analysis. Network graphs were then constructed in order to visualize the network, in which countries are the nodes, and the edges between nodes represent congruence between FA country and SS country for a given RCT. Statistical analyses and network visualization were undertaken using Python.

Results: There were 93 countries represented with 419 unique first author-study setting (FA-SS) pairs identified (fig 1). The median number of studies per pair was 1, and the maximum was 18. Outside of within-country associations, the most common FA-SS combinations were FAs in the U.S. and Canada with SSs in India and the U.S., respectively (>15 sites per pairing). Forty-five of the 93 countries were high income, 20 each were upper-middle or lower-middle income, and 7 were lower income. Ninety-five percent of studies took place in countries of the same World Bank income category as the FA (p < 0.001; fig 2).

Conclusion(s): The vast majority of neonatal RCTs demonstrate concordance between FA and SS countries, suggesting excellent prioritization of local representation in clinical trials. Future work will focus on further characterizing coauthorship networks by country and institution.

Global Network of Neonatal RCTs
Node color indicates World Bank income classification (red = high income; orange = upper middle income; yellow = lower middle income; green = low income; gray = unclassified).

First Author - Study Setting Concordance by World Bank Income Classification
HI = high income; LI = low income; LM = lower middle income; UM = upper middle income; WB = World Bank