PMID- 30622070
OWN - NLM
STAT- MEDLINE
DCOM- 20190610
LR  - 20190613
IS  - 1873-6750 (Electronic)
IS  - 0160-4120 (Linking)
VI  - 123
DP  - 2019 Feb
TI  - Low-calorie sweeteners and health outcomes: A demonstration of rapid evidence
      mapping (rEM).
PG  - 451-458
LID - S0160-4120(18)31646-5 [pii]
LID - 10.1016/j.envint.2018.11.070 [doi]
AB  - BACKGROUND: "Evidence Mapping" is an emerging tool that is increasingly being
      used to systematically identify, review, organize, quantify, and summarize the
      literature. It can be used as an effective method for identifying well-studied
      topic areas relevant to a broad research question along with any important
      literature gaps. However, because the procedure can be significantly
      resource-intensive, approaches that can increase the speed and reproducibility of
      evidence mapping are in great demand. METHODS: We propose an alternative process 
      called "rapid Evidence Mapping" (rEM) to map the scientific evidence in a
      time-efficient manner, while still utilizing rigorous, transparent and explicit
      methodological approaches. To illustrate its application, we have conducted a
      proof-of-concept case study on the topic of low-calorie sweeteners (LCS) with
      respect to human dietary exposures and health outcomes. During this process, we
      developed and made publicly available our study protocol, established a PECO
      (Participants, Exposure, Comparator, and Outcomes) statement, searched the
      literature, screened titles and abstracts to identify potentially relevant
      studies, and applied semi-automated machine learning approaches to tag and
      categorize the included articles. We created various visualizations including
      bubble plots and frequency tables to map the evidence and research gaps according
      to comparison type, population baseline health status, outcome group, and study
      sample size. We compared our results with a traditional evidence mapping of the
      same topic published in 2016 (Wang et al., 2016). RESULTS: We conducted an rEM of
      LCS, for which we identified 8122 records from a PubMed search (January 1,
      1946-May 1, 2014) and then utilized machine learning (SWIFT-Active Screener) to
      prioritize relevant records. After screening 2267 (28%) of the total set of
      titles and abstracts to achieve 95% estimated recall, we ultimately included 297 
      relevant studies. Overall, our findings corroborated those of Wang et al. (2016) 
      and identified that most studies were acute or short-term in healthy individuals,
      and studied the outcomes of appetite, energy sensing and body weight. We also
      identified a lack of studies assessing appetite and dietary intake related
      outcomes in people with diabetes. The rEM approach required approximately 100
      person-hours conducted over 7 calendar months. CONCLUSION: Rapid Evidence Mapping
      is an expeditious approach based on rigorous methodology that can be used to
      quickly summarize the available body of evidence relevant to a research question,
      identify gaps in the literature to inform future research, and contextualize the 
      design of a systematic review within the broader scientific literature,
      significantly reducing human effort while yielding results comparable to those
      from traditional methods. The potential time savings of this approach in
      comparison to the traditional evidence mapping process make it a potentially
      powerful tool for rapidly translating knowledge to inform science-based
      decision-making.
CI  - Copyright (c) 2018 Elsevier Ltd. All rights reserved.
FAU - Lam, Juleen
AU  - Lam J
AD  - Sciome LLC, RTP, NC, United States of America; California State University, East 
      Bay, Department of Health Sciences, Hayward, CA, United States of America.
      Electronic address: Juleen.Lam@sciome.com.
FAU - Howard, Brian E
AU  - Howard BE
AD  - Sciome LLC, RTP, NC, United States of America.
FAU - Thayer, Kristina
AU  - Thayer K
AD  - Integrated Risk Information System (IRIS) Division, National Center for
      Environmental Assessment, Environmental Protection Agency, Washington, DC, United
      States of America.
FAU - Shah, Ruchir R
AU  - Shah RR
AD  - Sciome LLC, RTP, NC, United States of America.
LA  - eng
PT  - Journal Article
PT  - Review
DEP - 20190105
PL  - Netherlands
TA  - Environ Int
JT  - Environment international
JID - 7807270
RN  - 0 (Sweetening Agents)
SB  - IM
MH  - Body Weight
MH  - *Health Status
MH  - Humans
MH  - Reproducibility of Results
MH  - *Review Literature as Topic
MH  - *Sweetening Agents
OTO - NOTNLM
OT  - *Artificial sweeteners
OT  - *Evidence map
OT  - *Evidence-based methodology
OT  - *Low calorie sweeteners
OT  - *Rapid evidence mapping
OT  - *Systematic review
EDAT- 2019/01/10 06:00
MHDA- 2019/06/14 06:00
CRDT- 2019/01/10 06:00
PHST- 2018/07/25 00:00 [received]
PHST- 2018/11/20 00:00 [revised]
PHST- 2018/11/27 00:00 [accepted]
PHST- 2019/01/10 06:00 [pubmed]
PHST- 2019/06/14 06:00 [medline]
PHST- 2019/01/10 06:00 [entrez]
AID - S0160-4120(18)31646-5 [pii]
AID - 10.1016/j.envint.2018.11.070 [doi]
PST - ppublish
SO  - Environ Int. 2019 Feb;123:451-458. doi: 10.1016/j.envint.2018.11.070. Epub 2019
      Jan 5.