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Record W4296673382 · doi:10.1016/j.jtocrr.2022.100383

Are We Underestimating Efficacy and Cost-Efficacy of Population Lung Cancer Computed Tomography Screening?

2022· editorial· en· W4296673382 on OpenAlexaboutno aff
Frederic W. Grannis

Bibliographic record

VenueJTO Clinical and Research Reports · 2022
Typeeditorial
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsComputed tomographyLung cancerLung cancer screeningMedicinePopulationRadiologyOncologyEnvironmental health

Abstract

fetched live from OpenAlex

In a perfect world, governments would allocate sufficient funds to provide optimal care for every patient with cancer. Sadly, this is not now the case. Legislators worldwide are parsimonious in funding for medical care, concerned that their constituents are loathe to pay more taxes. Accordingly, it is important for medical researchers to provide accurate information on cost and cost-effectiveness of new medical interventions, so that politicians and public health officials have accurate information to guide just and efficient allocation of funding to optimize medical care.Unfortunately, cost-effectiveness research has intrinsic problems. The methodology required to conduct such research is complex. Clinicians are well suited to provide input data on effectiveness of treatments, that is, duration of survival and quality of life, but are not typically skilled in evidence collection, economics, mathematical modeling, and biostatistics. Close collaboration between clinicians and methodologists is accordingly essential, if accurate information is to be published.Major variance in cost-effectiveness data has important public health implications. Facing a decision on what to spend, from a tight budget, legislators might be more generous if data inform that many more lives could be saved at substantially lower cost.The authors of “Expected Cost Savings From Low-Dose Computed Tomography Scan Screening for Lung Cancer in Alberta, Canada” have done a workman-like job of analyzing input data provided by clinicians and methodologists and have gotten the correct answer—computed tomography (CT) lung cancer screening is cost-effective.1Thanh N.X. Pham T.M. Waye A. et al.Expected cost savings from low-dose computed tomography scan screening for lung cancer in Alberta, Canada.JTO Clin Res Rep. 2022; 3100350PubMed Google Scholar So far, so good, but although the authors recommend CT screening for lung cancer as cost-effective, their estimate of the amount of the public health dollars saved in treating screen-detected, early stage lung cancer is probably far too small.Input data they use in their calculations do not reflect current clinical practice. It is important for readers to understand that effectiveness data often vary widely between studies. In the very specific case of lung cancer screening, there has been contentious disputation of risks, benefits, and costs for more than 20 years. For example, Bach and Gould2Bach P.B. Gould M.K. When the average applies to no one: personalized decision making about potential benefits of lung cancer screening.Ann Intern Med. 2012; 157: 571-573Crossref PubMed Google Scholar estimated that only one in five (21%) diagnosed by CT screening would achieve long-term survival. The corresponding figure in IELCAP research is greater than four in five (80%).3Henschke C.I. Yankelevitz D.F. Libby D.M. Pasmantier M.W. Smith J.P. Miettinen O.S. International Early Lung Cancer Early Action Program Investigators. Survival of patients with stage I lung cancer detected on CT screening.N Engl J Med. 2006; 355: 1763-1771Crossref PubMed Scopus (1451) Google Scholar In a 2015 update, long-term survival was substantially higher in IELCAP compared with National Lung Screening Trial (NLST) study subjects.4Yip R. Henschke C.I. Yankelevitz D.F. Boffetta P. Smith J.P. International Early Lung Cancer Investigators. The impact of the regimen of screening on lung cancer cure: a comparison of I-ELCAP and NLST.Eur J Cancer Prev. 2015; 24: 201-208Crossref PubMed Scopus (24) Google Scholar The range of published results for the cost of a quality-adjusted life-year varies nearly a thousand-fold, between $2500 (Wisnivesky)5Wisnivesky J.P. Mushlin A.I. Sicherman N. Henschke C. The cost-effectiveness of low-dose CT screening for lung cancer: preliminary results of baseline screening.Chest. 2003; 124: 614-621Abstract Full Text Full Text PDF PubMed Scopus (149) Google Scholar and $2 million (Bach)!What then is a cost-effectiveness researcher to do? What effectiveness data does he accept as valid to enter into his model? This question has plagued all past efforts at measuring cost-effectiveness of CT lung cancer screening.If a researcher chooses input effectiveness data derived from the IELCAP study, the cost of a quality-adjusted life-year derived from CT screening will be substantially lower than cost output from a researcher who selects NLST data. In this study, the investigators specifically incorporate NLST entry criteria and limit analysis to only three annual screens. This design will predictably yield poorer cost-effectiveness in comparison to an IELCAP design that prescribes annual CT screening in a longer duration.In NLST, as many as 2000 individuals died of lung cancer after CT screening had ceased, that is, after only three rounds of screening.6National Lung Screening Trial Research TeamLung cancer incidence and mortality with extended follow-up in the National Lung Screening Trial.J Thorac Oncol. 2019; 14: 1732-1742Abstract Full Text Full Text PDF PubMed Scopus (159) Google Scholar As we have argued elsewhere, data extrapolated from NLST grossly underestimate long-term survival and overestimate putative harms of lung cancer screening, including downstream costs associated with false-positive test results, overdiagnosis, unnecessary biopsies, and surgical operations.7Sands J. Tammemägi M.C. Couraud S. et al.Lung screening benefits and challenges: a review of the data and outline for implementation.J Thorac Oncol. 2021; 16: 37-53Abstract Full Text Full Text PDF PubMed Scopus (27) Google Scholar Because NLST did not incorporate a diagnostic or treatment algorithm, it had higher false-positives and higher rates of unnecessary biopsy and surgical operation for benign nodules.The Alberta investigators have correctly rejected the inaccurate (21%) estimate of long-term survival benefit from NLST, instead estimating that more than 70% will be diagnosed in stage 1 with high-commensurate long-term survival.How Might Researchers Surmount the Problem of Selection of Input Data Into Cost-Effectiveness Models?A number of years ago, I had the great privilege of working with a brilliant young premedical student, who designed a modeling spreadsheet that calculated 1500 different sets of cost-effectiveness output measures, on the basis of input of three sets of, respectively, high, median, and low estimates derived from review of multiple publications on lung cancer screening.8Castleberry A.W. Smith D. Anderson C. Rotter A.J. Grannis Jr., F.W. Cost of a 5-year lung cancer survivor: symptomatic tumour identification vs proactive computed tomography screening.Br J Cancer. 2009; 101: 882-896Crossref PubMed Scopus (17) Google Scholar,9Castleberry A.W. Grannis Jr., F.W. What is a reasonable cost to refute a preposterous hypothesis?.Br J Cancer. 2010; 102: 627-628Crossref PubMed Scopus (2) Google Scholar Anthony Castleberry’s method allows individual readers to reference cost-effectiveness using input data they deem appropriate and provides compelling data that—even using pessimistic assumptions—lung cancer screening outperforms treatment of symptomatic lung cancer, by a wide margin and has potential to prevent tens of thousands of lung cancer deaths and billions in health care expenditures. If our study were updated today, factoring in the far higher current costs of immunotherapy and other systemic therapies, relative cost-effectiveness of CT screening should prove substantially greater.One last consideration: unrealistic expectations and magical thinking about discovering a “Holy Grail” in molecular cancer screening may be contributing to delay in acceptance and implementation of—highly effective and relatively inexpensive—CT screening, in many nations. Costs of molecular cancer tests vary widely. Food and Drug Administration–approved FoundationOne CDx is priced at $5800.10Philippidis A. Breaking NGS ground. Gen: Genetic Engineering and Biotechnology News. May 22, 2018.https://www.genengnews.com/insights/breaking-ngs-ground/Date accessed: September 22, 2021Google Scholar Guardant Health 360 is approximately a thousand dollars more expensive. Grail’s Galleri test, sold under a “Clia waver,” is considerably less expensive, at $949.11Cairnes E. Grail launches pan-cancer screen—for those who can pay out of pocket.Evaluate Vantage. June 4, 2021; https://www.evaluate.com/vantage/articles/news/snippets/grail-launches-pan-cancer-screen-those-who-can-pay-out-pocketDate accessed: September 30, 2021Google Scholar Prescreening millions of individuals at elevated risk, at any comparable cost, is clearly impossible.It is imperative that we save lives (and dollars) by implementation of population CT screening—now.CRediT Authorship Contribution StatementFrederic W. Grannis, Jr. MD: It is the sole author. In a perfect world, governments would allocate sufficient funds to provide optimal care for every patient with cancer. Sadly, this is not now the case. Legislators worldwide are parsimonious in funding for medical care, concerned that their constituents are loathe to pay more taxes. Accordingly, it is important for medical researchers to provide accurate information on cost and cost-effectiveness of new medical interventions, so that politicians and public health officials have accurate information to guide just and efficient allocation of funding to optimize medical care. Unfortunately, cost-effectiveness research has intrinsic problems. The methodology required to conduct such research is complex. Clinicians are well suited to provide input data on effectiveness of treatments, that is, duration of survival and quality of life, but are not typically skilled in evidence collection, economics, mathematical modeling, and biostatistics. Close collaboration between clinicians and methodologists is accordingly essential, if accurate information is to be published. Major variance in cost-effectiveness data has important public health implications. Facing a decision on what to spend, from a tight budget, legislators might be more generous if data inform that many more lives could be saved at substantially lower cost. The authors of “Expected Cost Savings From Low-Dose Computed Tomography Scan Screening for Lung Cancer in Alberta, Canada” have done a workman-like job of analyzing input data provided by clinicians and methodologists and have gotten the correct answer—computed tomography (CT) lung cancer screening is cost-effective.1Thanh N.X. Pham T.M. Waye A. et al.Expected cost savings from low-dose computed tomography scan screening for lung cancer in Alberta, Canada.JTO Clin Res Rep. 2022; 3100350PubMed Google Scholar So far, so good, but although the authors recommend CT screening for lung cancer as cost-effective, their estimate of the amount of the public health dollars saved in treating screen-detected, early stage lung cancer is probably far too small. Input data they use in their calculations do not reflect current clinical practice. It is important for readers to understand that effectiveness data often vary widely between studies. In the very specific case of lung cancer screening, there has been contentious disputation of risks, benefits, and costs for more than 20 years. For example, Bach and Gould2Bach P.B. Gould M.K. When the average applies to no one: personalized decision making about potential benefits of lung cancer screening.Ann Intern Med. 2012; 157: 571-573Crossref PubMed Google Scholar estimated that only one in five (21%) diagnosed by CT screening would achieve long-term survival. The corresponding figure in IELCAP research is greater than four in five (80%).3Henschke C.I. Yankelevitz D.F. Libby D.M. Pasmantier M.W. Smith J.P. Miettinen O.S. International Early Lung Cancer Early Action Program Investigators. Survival of patients with stage I lung cancer detected on CT screening.N Engl J Med. 2006; 355: 1763-1771Crossref PubMed Scopus (1451) Google Scholar In a 2015 update, long-term survival was substantially higher in IELCAP compared with National Lung Screening Trial (NLST) study subjects.4Yip R. Henschke C.I. Yankelevitz D.F. Boffetta P. Smith J.P. International Early Lung Cancer Investigators. The impact of the regimen of screening on lung cancer cure: a comparison of I-ELCAP and NLST.Eur J Cancer Prev. 2015; 24: 201-208Crossref PubMed Scopus (24) Google Scholar The range of published results for the cost of a quality-adjusted life-year varies nearly a thousand-fold, between $2500 (Wisnivesky)5Wisnivesky J.P. Mushlin A.I. Sicherman N. Henschke C. The cost-effectiveness of low-dose CT screening for lung cancer: preliminary results of baseline screening.Chest. 2003; 124: 614-621Abstract Full Text Full Text PDF PubMed Scopus (149) Google Scholar and $2 million (Bach)! What then is a cost-effectiveness researcher to do? What effectiveness data does he accept as valid to enter into his model? This question has plagued all past efforts at measuring cost-effectiveness of CT lung cancer screening. If a researcher chooses input effectiveness data derived from the IELCAP study, the cost of a quality-adjusted life-year derived from CT screening will be substantially lower than cost output from a researcher who selects NLST data. In this study, the investigators specifically incorporate NLST entry criteria and limit analysis to only three annual screens. This design will predictably yield poorer cost-effectiveness in comparison to an IELCAP design that prescribes annual CT screening in a longer duration. In NLST, as many as 2000 individuals died of lung cancer after CT screening had ceased, that is, after only three rounds of screening.6National Lung Screening Trial Research TeamLung cancer incidence and mortality with extended follow-up in the National Lung Screening Trial.J Thorac Oncol. 2019; 14: 1732-1742Abstract Full Text Full Text PDF PubMed Scopus (159) Google Scholar As we have argued elsewhere, data extrapolated from NLST grossly underestimate long-term survival and overestimate putative harms of lung cancer screening, including downstream costs associated with false-positive test results, overdiagnosis, unnecessary biopsies, and surgical operations.7Sands J. Tammemägi M.C. Couraud S. et al.Lung screening benefits and challenges: a review of the data and outline for implementation.J Thorac Oncol. 2021; 16: 37-53Abstract Full Text Full Text PDF PubMed Scopus (27) Google Scholar Because NLST did not incorporate a diagnostic or treatment algorithm, it had higher false-positives and higher rates of unnecessary biopsy and surgical operation for benign nodules. The Alberta investigators have correctly rejected the inaccurate (21%) estimate of long-term survival benefit from NLST, instead estimating that more than 70% will be diagnosed in stage 1 with high-commensurate long-term survival. How Might Researchers Surmount the Problem of Selection of Input Data Into Cost-Effectiveness Models?A number of years ago, I had the great privilege of working with a brilliant young premedical student, who designed a modeling spreadsheet that calculated 1500 different sets of cost-effectiveness output measures, on the basis of input of three sets of, respectively, high, median, and low estimates derived from review of multiple publications on lung cancer screening.8Castleberry A.W. Smith D. Anderson C. Rotter A.J. Grannis Jr., F.W. Cost of a 5-year lung cancer survivor: symptomatic tumour identification vs proactive computed tomography screening.Br J Cancer. 2009; 101: 882-896Crossref PubMed Scopus (17) Google Scholar,9Castleberry A.W. Grannis Jr., F.W. What is a reasonable cost to refute a preposterous hypothesis?.Br J Cancer. 2010; 102: 627-628Crossref PubMed Scopus (2) Google Scholar Anthony Castleberry’s method allows individual readers to reference cost-effectiveness using input data they deem appropriate and provides compelling data that—even using pessimistic assumptions—lung cancer screening outperforms treatment of symptomatic lung cancer, by a wide margin and has potential to prevent tens of thousands of lung cancer deaths and billions in health care expenditures. If our study were updated today, factoring in the far higher current costs of immunotherapy and other systemic therapies, relative cost-effectiveness of CT screening should prove substantially greater.One last consideration: unrealistic expectations and magical thinking about discovering a “Holy Grail” in molecular cancer screening may be contributing to delay in acceptance and implementation of—highly effective and relatively inexpensive—CT screening, in many nations. Costs of molecular cancer tests vary widely. Food and Drug Administration–approved FoundationOne CDx is priced at $5800.10Philippidis A. Breaking NGS ground. Gen: Genetic Engineering and Biotechnology News. May 22, 2018.https://www.genengnews.com/insights/breaking-ngs-ground/Date accessed: September 22, 2021Google Scholar Guardant Health 360 is approximately a thousand dollars more expensive. Grail’s Galleri test, sold under a “Clia waver,” is considerably less expensive, at $949.11Cairnes E. Grail launches pan-cancer screen—for those who can pay out of pocket.Evaluate Vantage. June 4, 2021; https://www.evaluate.com/vantage/articles/news/snippets/grail-launches-pan-cancer-screen-those-who-can-pay-out-pocketDate accessed: September 30, 2021Google Scholar Prescreening millions of individuals at elevated risk, at any comparable cost, is clearly impossible.It is imperative that we save lives (and dollars) by implementation of population CT screening—now. A number of years ago, I had the great privilege of working with a brilliant young premedical student, who designed a modeling spreadsheet that calculated 1500 different sets of cost-effectiveness output measures, on the basis of input of three sets of, respectively, high, median, and low estimates derived from review of multiple publications on lung cancer screening.8Castleberry A.W. Smith D. Anderson C. Rotter A.J. Grannis Jr., F.W. Cost of a 5-year lung cancer survivor: symptomatic tumour identification vs proactive computed tomography screening.Br J Cancer. 2009; 101: 882-896Crossref PubMed Scopus (17) Google Scholar,9Castleberry A.W. Grannis Jr., F.W. What is a reasonable cost to refute a preposterous hypothesis?.Br J Cancer. 2010; 102: 627-628Crossref PubMed Scopus (2) Google Scholar Anthony Castleberry’s method allows individual readers to reference cost-effectiveness using input data they deem appropriate and provides compelling data that—even using pessimistic assumptions—lung cancer screening outperforms treatment of symptomatic lung cancer, by a wide margin and has potential to prevent tens of thousands of lung cancer deaths and billions in health care expenditures. If our study were updated today, factoring in the far higher current costs of immunotherapy and other systemic therapies, relative cost-effectiveness of CT screening should prove substantially greater. One last consideration: unrealistic expectations and magical thinking about discovering a “Holy Grail” in molecular cancer screening may be contributing to delay in acceptance and implementation of—highly effective and relatively inexpensive—CT screening, in many nations. Costs of molecular cancer tests vary widely. Food and Drug Administration–approved FoundationOne CDx is priced at $5800.10Philippidis A. Breaking NGS ground. Gen: Genetic Engineering and Biotechnology News. May 22, 2018.https://www.genengnews.com/insights/breaking-ngs-ground/Date accessed: September 22, 2021Google Scholar Guardant Health 360 is approximately a thousand dollars more expensive. Grail’s Galleri test, sold under a “Clia waver,” is considerably less expensive, at $949.11Cairnes E. Grail launches pan-cancer screen—for those who can pay out of pocket.Evaluate Vantage. June 4, 2021; https://www.evaluate.com/vantage/articles/news/snippets/grail-launches-pan-cancer-screen-those-who-can-pay-out-pocketDate accessed: September 30, 2021Google Scholar Prescreening millions of individuals at elevated risk, at any comparable cost, is clearly impossible. It is imperative that we save lives (and dollars) by implementation of population CT screening—now. CRediT Authorship Contribution StatementFrederic W. Grannis, Jr. MD: It is the sole author. Frederic W. Grannis, Jr. MD: It is the sole author.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.213
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.146
GPT teacher head0.510
Teacher spread0.365 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2022
Admission routes1
Has abstractyes

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