Evidence map›Paper›PMID 32758462›Full record

ArticleThe Lancet. Oncology2020

Estimating the impact of treatment and imaging modalities on 5-year net survival of 11 cancers in 200 countries: a simulation-based analysis.

Zachary J Ward, Andrew M Scott, Hedvig Hricak, May Abdel-Wahab, Diana Paez, Miriam Mikhail Lette, H Alberto Vargas, T Peter Kingham, Rifat Atun

Open access · greenAbstract read
In one paragraph

Article in The Lancet. Oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 2 pooled it
4.7field-weighted citation impact, top 4% of its field
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

41 citing papers in PubMed, 2 syntheses or guidelines pooled it, 59 citations in OpenAlex.

  1. Pooled it
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  5. A Scoping Review on Calibration Methods for Cancer Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
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  10. Nuclear medicine imaging in non-seminomatous germ cell tumors: lessons learned from the past failures.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
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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

9 authors at 5 institutions in 3 countries.

Zachary J WardCenter for Health Decision Science, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA. Electronic address: zward@hsph.harvard.edu.
Andrew M ScottOlivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia; Department of Molecular Imaging and Therapy, Austin Health, Melbourne, VIC, Australia; School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia; Department of Medicine, University of Melbourne, Melbourne, VIC, Australia.
Hedvig HricakDepartment of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
May Abdel-WahabInternational Atomic Energy Agency Department of Nuclear Sciences and Applications, Division of Human Health, Nuclear Medicine and Diagnostic Imaging Section, Vienna, Austria.
Diana PaezInternational Atomic Energy Agency Department of Nuclear Sciences and Applications, Division of Human Health, Nuclear Medicine and Diagnostic Imaging Section, Vienna, Austria.
Miriam Mikhail LetteInternational Atomic Energy Agency Department of Nuclear Sciences and Applications, Division of Human Health, Nuclear Medicine and Diagnostic Imaging Section, Vienna, Austria.
H Alberto VargasDepartment of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
T Peter KinghamDepartment of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Rifat AtunDepartment of Global Health and Population, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA; Department of Global Health and Social Medicine, Harvard Medical School, Harvard University, Boston, MA, USA.
International Atomic Energy Agency · ATMemorial Sloan Kettering Cancer Center · USAustin Health · AUHarvard Global Health Institute · USHarvard University · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

backgroundAccurate survival estimates are important for cancer control planning. Although observed survival estimates are unavailable for many countries, where they are available, wide variations are reported. Understanding the impact of specific treatment and imaging modalities can help decision makers to effectively allocate resources to improve cancer survival in their local context.

methodsWe developed a microsimulation model of stage-specific cancer survival in 200 countries and territories for 11 cancers (oesophagus, stomach, colon, rectum, anus, liver, pancreas, lung, breast, cervix uteri, and prostate) comprising 60% of global diagnosed cancer cases. The model accounts for country-specific availability of treatment (chemotherapy, surgery, radiotherapy, and targeted therapy) and imaging modalities (ultrasound, x-ray, CT, MRI, PET, single-photon emission CT), as well as quality of care. We calibrated the model to reported survival estimates from CONCORD-3 (which reports global trends in cancer survival in 2000-14). We estimated 5-year net survival for diagnosed cancers in each country or territory and estimated potential survival gains from increasing the availability of individual treatment and imaging modalities, and more comprehensive packages of scale-up of these interventions. We report the mean and 95% uncertainty intervals (UIs) for all outcomes, calculated as the 2·5 and 97·5 percentiles of the simulation results.

findingsThe estimated global 5-year net survival for all 11 cancers combined is 42·6% (95% uncertainty interval 40·3-44·3), with survival in high-income countries being an average of 12 times (range 4-17) higher than that in low-income countries. Expanding availability of surgery or radiotherapy or improving quality of care would yield the largest survival gains in low-income (2·5-3·4 percentage point increase in survival) and lower-middle-income countries (2·4-6·1 percentage point increase), whereas upper-middle-income and high-income countries are more likely to benefit from improved availability of targeted therapy (0·7 percentage point increase for upper-middle income and 0·4 percentage point increase for high income). Investing in medical imaging will also be necessary to achieve substantial survival gains, with traditional modalities estimated to provide the largest gains in low-income settings, while MRI and PET would yield the largest gains in higher-income countries. Simultaneous expansion of treatment, imaging, and quality of care could improve 5-year net survival by more than ten times in low-income countries (3·8% [95% UI 0·5-9·2] to 45·2% [40·2-52·1]) and could more than double 5-year net survival in lower-middle-income countries (20·1% [7·2-31·7] to 47·1% [42·8-50·8]).

interpretationScaling up both treatment and imaging availability could yield synergistic survival gains for patients with cancer. Expanding traditional modalities in lower-income settings might be a feasible pathway to improve survival before scaling up more modern technologies.

fundingHarvard T H Chan School of Public Health.

Indexed as

Survival AnalysisDeveloped CountriesDeveloping CountriesGlobal HealthHumansModels, StatisticalNeoplasms

Identifiers

PMID32758462
PMCPMC8020599
OpenAlexW3047200633

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.