Pandemic Quietly Eroded Timely Breast Cancer Care at Mexico’s Leading Cancer Center

When the SARS-CoV-2 pandemic swept through Mexico in 2020, hospitals in Mexico City transformed almost overnight. Wards were converted, operating rooms were reprioritized, and outpatient services were throttled back as staff and resources were diverted to the surging COVID-19 caseload. For women newly diagnosed with breast cancer, those systemic shifts carried a potentially life-altering consequence: the risk that the interval between learning their diagnosis and starting treatment would stretch beyond the window clinicians consider safe. A new retrospective study from Mexico’s National Cancer Institute, known as INCAN, offers one of the most detailed looks yet at how the pandemic reshaped that critical interval in a middle-income country, and its findings reveal a subtler story than raw averages suggest.

The research, published in Cancer Causes & Control, analyzed the records of 425 women treated at INCAN between November 2017 and December 2021, a window that captures roughly two and a half years of pre-pandemic care and the first two years of the pandemic itself. All patients were experiencing breast cancer for the first time, and all had complete documentation of the dates of both diagnosis and the start of treatment. The investigators calculated the diagnosis-to-treatment interval, or DTI, for every patient in days, and defined timely care as the initiation of treatment within 30 days of diagnosis, a benchmark consistent with international quality standards for breast cancer management.

On the surface, the headline numbers look almost reassuring. Among the 425 women, the median DTI was 18 days for those who began treatment on time, with an interquartile range of 14 to 24 days, while patients classified as delayed had a median interval of 42 days, spanning an interquartile range of 35 to 55 days. Comparing the two eras of care, the median DTI was 28 days before the pandemic and 23.5 days during it. The proportion of women starting treatment within the 30-day target was statistically indistinguishable between periods: 58.7 percent before the pandemic versus 61.9 percent during it, a difference the investigators tested and found non-significant at P equal to 0.509. If the analysis had stopped there, one might conclude that Mexico City’s flagship cancer hospital weathered the pandemic with its treatment pipelines intact.

But the raw comparison of periods conceals a more complicated reality, and the study’s multivariable analysis is where the pandemic’s fingerprint becomes visible. When the researchers adjusted for other factors influencing timeliness, receiving care during the pandemic was independently associated with roughly half the odds of timely treatment compared with the pre-pandemic era, with an adjusted odds ratio of 0.54 and a 95 percent confidence interval of 0.33 to 0.88, reaching statistical significance at P equal to 0.014. In other words, even though the overall proportion of timely cases appeared stable, women treated during the pandemic faced systematically higher risk of slipping past the 30-day threshold once the composition of the patient population and other influencing variables were taken into account. This kind of divergence between crude and adjusted estimates is a classic signal in epidemiology: it suggests the pandemic disrupted care in ways that were unevenly distributed across patient subgroups rather than uniformly lengthening everyone’s wait.

The most striking determinant of timeliness in the study was not the calendar but the type of first treatment a patient received. Women who began their treatment course with chemotherapy had dramatically higher odds of meeting the 30-day target than those who started with surgery, with an adjusted odds ratio of 19.77 and a 95 percent confidence interval of 5.23 to 74.62, a result significant at P less than 0.001. Hormone therapy as the initial treatment also conferred an advantage, with an adjusted odds ratio of 2.79 and a 95 percent confidence interval of 1.14 to 6.85, significant at P equal to 0.024. The clinical logic behind this gap is rooted in logistics. Chemotherapy and endocrine therapy can be initiated in an outpatient setting once a diagnosis is confirmed and a treatment plan is made, whereas surgery requires an available operating room, anesthesia capacity, a surgical team, and a hospital bed, all resources that the pandemic squeezed hardest.

The study also quantified, with unusual precision, the cost of referral friction. Each additional day that elapsed between a patient’s first consultation and her referral to medical oncology reduced the odds of timely treatment by roughly 1 percent, with a per-day odds ratio of 0.99 and a 95 percent confidence interval of 0.98 to 0.99, significant at P equal to 0.005. That may sound like a small effect for a single day, but compounded across the weeks that often separate a first visit from a specialist handoff, the cumulative impact is substantial. Referral pathways are among the least glamorous components of cancer care, yet this analysis shows they are among the most consequential: the journey of a paperwork packet between departments can determine whether a woman begins potentially curative therapy within the recommended month or watches the clock run past it.

Socioeconomic status emerged as another meaningful axis of inequality. In the bivariate analysis, women of high socioeconomic status had lower odds of timely treatment than those of low status, with an odds ratio of 0.36 and a 95 percent confidence interval of 0.14 to 0.96, significant at P equal to 0.042. The authors note this counterintuitive pattern, and while the underlying mechanisms warrant further investigation, it underscores that timeliness in a centralized referral system does not map neatly onto wealth. Patients arriving at a national reference center come through many routes, and the study’s broader message is that institutional process, not patient resources alone, drives how quickly treatment begins once someone enters the system.

The findings sit within a global literature documenting pandemic-era disruption of cancer services. Studies from the Netherlands, France, Australia, and the United States reported surgical delays, shifts toward neoadjuvant systemic therapy, and temporary drops in screening diagnoses during 2020 and 2021. What distinguishes the INCAN analysis is its setting and its methodological candor. In a middle-income country where diagnosis-to-treatment delays were already recognized as a persistent challenge before 2020, the pandemic arrived as a stress test on a system operating without slack. The fact that median intervals actually shortened slightly during the pandemic years, while adjusted odds of timeliness fell, illustrates how aggregate statistics can mask the experiences of the subset of patients who bore the brunt of disruption.

That subset matters clinically. Prior research cited in the study, including population-based cohorts from Queensland, Australia, and surgical oncology analyses from the United States, links longer treatment intervals with inferior survival in breast cancer. A delayed patient in this Mexican cohort faced a median wait of 42 days, two full weeks beyond the timeliness threshold, and the authors describe these delays as clinically relevant. International guideline bodies, including EUSOMA and ESMO, treat time to first treatment as a core quality indicator precisely because it is modifiable: it reflects scheduling, coordination, and decision-making speed rather than tumor biology.

Perhaps the most practical takeaway from the INCAN team is their argument that the fixes identified require no new infrastructure. Because the dominant predictors of delay were referral logistics and the choice of first treatment modality, streamlining the pathway from first consultation to medical oncology, and protecting surgical capacity so that patients whose optimal first treatment is an operation are not funneled into prolonged queues, could restore timeliness even under conditions of severe system stress. As health systems worldwide continue absorbing the aftershocks of the pandemic, this Mexico City cohort study serves as a reminder that resilience in cancer care is built in the seams between departments, in the speed of a referral, and in the days that pass, each one quietly eroding a patient’s odds, between diagnosis and the first dose of treatment.

Subject of Research: The effect of the SARS-CoV-2 pandemic on the diagnosis-to-treatment interval for breast cancer patients at a reference cancer center in Mexico City

Article Title: Effect of the SARS-CoV-2 pandemic on the opportunity to treat patients with breast cancer: experience at a reference cancer center in Mexico City

Article References: Effect of the SARS-CoV-2 pandemic on the opportunity to treat patients with breast cancer: experience at a reference cancer center in Mexico City. (n.d.). https://doi.org/10.1007/s10552-026-02235-z

Image Credits: AI Generated

DOI: 10.1007/s10552-026-02235-z

Keywords: breast cancer, SARS-CoV-2, COVID-19 pandemic, treatment delay, diagnosis-to-treatment interval, Mexico, National Cancer Institute, oncology, health services research, surgery, chemotherapy, health equity