The Hidden Cost of Cancer Care: How Much of Patients’ Lives Is Lost to Treatment Time?

Every hour a person with cancer spends in a waiting room, on an infusion chair, or in a hospital bed is an hour not spent at home, at work, or with the people they love. Oncologists have a name for this increasingly recognized burden: time toxicity. The concept, which captures the sheer volume of time that cancer care consumes from patients and their families, has moved rapidly from a provocative editorial idea to a measurable outcome in clinical research. Yet a new systematic review suggests that the field is measuring it in wildly inconsistent ways, and almost never by asking patients themselves what their time is worth.

The review, published in Supportive Care in Cancer by Ian Jun Yan Wee of Singapore General Hospital and colleagues, systematically searched the MEDLINE, EMBASE, and Cochrane Library databases from their inception through March 10, 2026. The team included studies that involved cancer patients and reported a definable measure of time-related burden associated with care. Fifty-six studies made the final cut, and their collective picture is one of a young research field growing fast but without a shared vocabulary or a common yardstick.

The technical details of what the reviewers found are revealing. The overwhelming majority of included studies, 45 of 56 or 80.4 percent, were observational in design, and nearly all were conducted in high-income countries, with the United States alone accounting for 29 studies, or 51.8 percent of the total. That geographic concentration matters, because the time burden of cancer care depends heavily on health system structure: how far patients must travel, how centralized specialist care is, and how efficiently clinics are run. Findings from American health systems may not translate cleanly to Europe, Asia, or low- and middle-income settings where the logistics of care can look radically different.

More striking still is how time toxicity was actually defined. The most common approach, used in 31 studies or 55.4 percent, relied on direct healthcare time measures: counting the days on which a patient had any healthcare encounter, whether a clinic visit, a treatment session, a hospitalization, or an emergency department visit. This metric, often called healthcare contact days, treats any calendar day touched by the medical system as a day partially consumed by it. It is elegant in its simplicity and easy to compute from routine data, but it is also a blunt instrument. A fifteen-minute blood draw and an eight-hour infusion day count identically.

A second family of measures, used in 20 studies or 35.7 percent, inverts the logic. Instead of counting days lost to care, these studies count time away from healthcare: days alive and out of hospital, or days spent at home. This approach, which has gained particular traction in surgical oncology, where it has been applied to procedures ranging from lung lobectomy to ovarian cancer surgery to colorectal resections, frames the outcome in terms patients might actually value: how much of their remaining life is spent in their own beds rather than institutional ones. Studies in the review applied it to acute myeloid leukemia, spinal metastases, and end-of-life cancer care, among other settings.

A third and much smaller category, appearing in just 5 studies or 8.9 percent, captured healthcare process time: the non-clinical and logistical dimensions of care, such as travel, waiting, scheduling, and coordination. These are the invisible hours that rarely appear in any medical record but can dominate a patient’s week, particularly for those in rural areas or those navigating fragmented systems. One Italian study cited in the review found that delivering treatment closer to patients’ homes reduced travel burden and time toxicity while improving satisfaction, a finding that illustrates how logistical design choices have real clinical consequences.

Perhaps the most consequential finding of the review is what was missing. Not a single study used a patient-reported definition of time toxicity. Every one of the 56 studies derived its measures from administrative databases, electronic health records, or clinical trial data. These sources are excellent at capturing healthcare utilization, but they are structurally incapable of capturing what patients perceive: whether a day at the hospital felt like a burden or a relief, whether the time was worth the benefit, or how the hours of care ripple through caregiving, employment, and family life. Prior qualitative work by some of the same researchers cited in the review has shown that patients, caregivers, and clinicians all recognize time burdens, but that recognition has not yet been translated into standardized patient-reported measures.

This gap matters because time toxicity is fundamentally a question of value, not just volume. In oncology, where treatments with marginal survival benefits are common, the trade-off between weeks of life gained and days of life consumed is not hypothetical. Research cited in the review has shown that patients do weigh time toxicity when assessing treatments with marginal benefit, and that the burden is unequally distributed, falling hardest on patients who live far from treatment centers, those without flexible jobs, and those without caregivers to drive them to appointments. A metric built purely from billing codes cannot see any of this.

To address the fragmentation, the review’s authors propose an empirical framework built on three objective measurement domains: direct healthcare time, time away from healthcare, and healthcare process time. Crucially, they position patient-reported experience not as a replacement for these objective measures but as an evidence-informed extension of them. The framework is an attempt to give the field a common architecture, so that a contact-day analysis in lung cancer and a days-at-home analysis in myeloma can eventually be compared, pooled, and translated into clinical decision-making. Standardization of this kind is a prerequisite for time toxicity to enter formal health technology assessment, where it could influence which treatments are funded and how care is delivered.

The implications reach well beyond academic taxonomy. As systemic therapies proliferate and survival improves for many cancers, the cumulative time burden of monitoring, imaging, infusions, and follow-up visits grows in parallel. Interventions already visible in the literature, from streamlined preoperative clinics to text-message interventions designed to minimize the time burden of care, to the substitution of subcutaneous for intravenous formulations of drugs, show that time toxicity is modifiable. But to modify it systematically, clinicians and policymakers first need to measure it consistently. This review makes clear that the field has taken the first step, cataloguing what exists, and the second, proposing a framework, but the hardest work remains: building measures that reflect not just how many days the healthcare system touches, but what those days cost the people living through them.

Subject of Research: Definitions and measurement methods of time toxicity in cancer care

Article Title: Time toxicity in cancer care: a systematic review of definitions and measurement methods

Article References: Time toxicity in cancer care: a systematic review of definitions and measurement methods. (n.d.). https://doi.org/10.1007/s00520-026-11283-9

Image Credits: AI Generated

DOI: 10.1007/s00520-026-11283-9

Keywords: time toxicity, cancer care, systematic review, supportive care, healthcare contact days, days alive and out of hospital, patient-reported outcomes, oncology, treatment burden, health services research, electronic health records, palliative care