In a response to the comment, the study authors wrote that “we agree that the lack of breast cancer screening in men could be one reason why men had higher mortality than women,” but argued that lead-time bias isn’t a major factor in the overall differences.4 To Dr Euler-Chelpin, the response made little sense. “They don’t talk about survival, they talk about mortality,” a measure that is unaffected by lead-time bias, she said.

Some researchers have attempted to rule out lead-time bias in cancer screening studies that rely on survival metrics, for instance, by controlling for the stage of the tumor at diagnosis and death.5 Others have developed theoretical models to try and correct for lead-time bias, or try to otherwise account for the lead time within their study designs.6,3 But because it’s impossible to know exactly what the lead time is for each patient, such corrections are imperfect, Dr Euler-Chelpin noted.

She advised using mortality measures, rather than survival, for comparing screening success across populations with different levels of screening.

Lead-time bias can also be an issue when discussing the development of new screening methods, for instance, for detecting disease recurrence following drug therapy.

Another recent study examined the efficacy of detecting circulating tumor DNA (ctDNA) in 101 patients who had undergone initial therapy for early-stage breast cancer and who had a high risk of recurrence.7 The authors found that ctDNA levels in patient plasma was prognostic of future relapse; 23 of 29 patients who suffered relapse tested positive for ctDNA, and the mean lead time between the detection of ctDNA and patient relapse was 10.7 months.

Though the study validates ctDNA detection as a method for evaluating the probability of recurrence, some in the field questioned “whether 10.7 months’ lead time of early detection of recurrence will save lives at all.”8

Garvit Chitkara, MBBS, DNB, assistant professor of breast surgical oncology in the breast disease management group at the Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, India, and a coauthor of the comment, argued that there’s no evidence that such detection would result in clinically meaningful improvements.

Dr Chitkara pointed to 2 randomized clinical trials published in the 1990s, in which researchers investigated whether follow-up through X-ray or ultrasound of patients with early-stage breast cancer following initial therapy would bring clinical benefit. Although the tests resulted in 6 months of lead time, earlier diagnosis of recurrence and ensuing treatment did not result in improved survival, he explained.

Based on those earlier findings, “it’s very difficult to say that this lead time of 10.7 months is actually going to show a clinically meaningful benefit,” he said.

Long-term follow-up studies will be key to rule out lead-time bias, and that applies across all cancer settings, noted Fred Grannis, MD, clinical professor of thoracic surgery at the City of Hope National Medical Center in Duarte, California.

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When several clinical studies in the 1990s showed considerable survival gains in patients who were screened for lung cancer — with no immediate reduction in lung cancer-specific mortality — researchers hypothesized that this was largely due to lead-time bias, overdiagnosis bias, and length-time bias. To Dr Grannis, these are dangerous theories that have delayed the implementation of population-wide lung cancer screening.9

However, results from long-term follow-up studies have documented a significant drop in mortality among screened cohorts, which to Dr Grannis, convincingly refutes the lead-time bias hypothesis. “There may be some lead-time bias, but it’s very small in the case of lung cancer. In the case[s] of breast cancer and prostate cancer, it may be more than that,” he said.

Ultimately, for clinicians, “the most important [thing] is to be aware of [lead-time bias],” Dr Euler-Chelpin concluded. If you’re a clinician and you’re keeping up to date with best practices, she added, that means you must have a critical eye on the possibility that lead-time bias could be something to consider when making study conclusions. Physicians must be “aware that this exists and … to spot whether it’s been taken into account or not.”

References

  1. Wang F, Shu X, Meszoely I, et al. Overall mortality after diagnosis of breast cancer in men vs women. JAMA Oncol. 2019;5(11):1589-1596.
  2. Euler-Chelpin, M. Lead-time bias in the analyses of overall mortality of breast cancer in men vs women. JAMA Oncol. 2020;6(3):441–442.
  3. Abrahamsson L, Isheden G, Czene K, Humphreys K. Continuous tumour growth models, lead time estimation and length bias in breast cancer screening studies. ‎Stat Methods Med Res. 2020;29(2):374-395.
  4. Wang F, Xiao-Ou S. Lead-time bias in the analyses of overall mortality of breast cancer in men vs women—reply. JAMA Oncol. 2020;6(3):442.
  5. Olén O, Erichsen R, Sachs MC, et al. Colorectal cancer in Crohn’s disease: a Scandinavian population-based cohort study [published online February 14, 2020]. Lancet Gastroenterol Hepatol. doi: 10.1016/S24681253(20)30005-4
  6. Duffy SW, Nagtegaal IR, Wallis M, et al. Correcting for lead time and length bias in estimating the effect of screen detection on cancer survival. Am J Epidemiol. 2008;168(1):98-104.
  7. Garcia-Murillas I, Chopra N, Comino-Méndez I, et al. Assessment of molecular relapse detection in early-stage breast cancer. JAMA Oncol. 2019;5(10):1473-1478.
  8. Chitara G, Hawaldar R, Badwe RA. Clinical benefit of circulating tumor DNA analysis in early-stage breast cancer. JAMA Oncol. 2020;6(3):439–440.
  9. Grannis FW. Lung cancer incidence and mortality with extended follow-up during screening. J Thorac Oncol. 2019;14(10):1692-1694.