Evidence map›Paper›PMID 19077266›Full record

ArticleImmunome research2008

Data mining of cancer vaccine trials: a bird's-eye view.

Xiaohong Cao, Karen B Maloney, Vladimir Brusic

Abstract read
In one paragraph

Article in Immunome research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xiaohong CaoBabson College, Wellesley, MA, USA. xiaohong.cao@gmail.com
Karen B Maloney
Vladimir Brusic

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA wealth of information on clinical trials has been provided by publicly accessible online registries. Information technology and data exchange standards enable rapid extraction, summarization, and visualization of information and derived knowledge from these data sets. Clinical trials data was extracted in the XML format from the National Library of Medicine ClinicalTrials.gov site. This data includes categories such as 'Summary of Purpose', 'Trial Sponsor', 'Phase of the Trial', 'Recruiting Status', and 'Location'. We focused on 645 clinical trials related to cancer vaccines. Additional facts on cancer types, including incidence and survival rates, were retrieved from the National Cancer Institute Surveillance data.

resultsThis application enables rapid extraction of information about institutions, diseases, clinical approaches, clinical trials dates, predominant cancer types in the trials, clinical opportunities and pharmaceutical market coverage. Presentation of results is facilitated by visualization tools that summarize the landscape of ongoing and completed cancer vaccine trials. Our summaries show the number of clinical vaccine trials per cancer type, over time, by phase, by lead sponsors, as well as trial activity relative to cancer type and survival data. We also have identified cancers that are neglected in the cancer vaccine field: bladder, liver, pancreatic, stomach, esophageal, and all of the low-incidence cancers.

conclusionWe have developed a data mining approach that enables rapid extraction of complex data from the major clinical trial repository. Summarization and visualization of these data represents a cost-effective means of making informed decisions about future cancer vaccine clinical trials.

Identifiers

PMID19077266
PMCPMC2639543

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.