Evidence map›Paper›PMID 38525348›Full record

ArticlePreventive oncology & epidemiology2023

Cancer Research in 2030: A unique strategic planning process at a comprehensive cancer center.

Erin M Bank, Eric J Small, Alan Ashworth, Robert A Hiatt

Abstract read
In one paragraph

Article in Preventive oncology & epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Erin M BankHelen Diller Family Comprehensive Cancer Center, University of California, San Francisco, United States.
Eric J SmallHelen Diller Family Comprehensive Cancer Center, University of California, San Francisco, United States.
Alan AshworthHelen Diller Family Comprehensive Cancer Center, University of California, San Francisco, United States.
Robert A HiattHelen Diller Family Comprehensive Cancer Center, University of California, San Francisco, United States.

Funding

Translational InformaticsP30CA082103 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Kate Taylor Shumate · 1999 to 2026
$209.7M
NCI NIH HHS P30 CA082103
6 · The paper itself

Abstract

Following the successful renewal of its Cancer Center Support Grant (CCSG), leadership of the UCSF Helen Diller Comprehensive Cancer Center (HDFCCC) began a strategic planning process. The motivation was to think about where cancer research was going in the future; and with this vision to define a general scientific direction, mission, and priorities. HDFCCC Leadership began discussions about a new strategic plan in early 2018. From these meetings, the theme of "Cancer Research in 2030" arose: that is, what will cancer research look like in 2030? This forward-looking focus was intended to encourage creativity unconfined by a particular institutional structure or grant mechanism. Focusing on the science paved the way for an innovative, actionable, and motivating strategic planning process. Here, we describe the three-phase process, and the various groups involved across the HDFCCC and UCSF. We present the unique framework based on a cells-to-society model and an individual experience perspective, which led to the development of a logic model and ongoing implementation of tactics and tracking progress. We believe that sharing this process and its results will be of value to cancer centers and cancer researchers across the network of NCI comprehensive cancer centers, and cancer research centers in general.

Indexed as

comprehensive cancer centerStrategic planning

Identifiers

PMID38525348
PMCPMC10959521

What OpenQuestion holds

Textmetadata
LicenceTDM
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Registered trials

None linked

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.