30-day mortality after systemic anticancer treatment for breast and lung cancer in England: a population-based, observational study

Abstract

Background: 30-day mortality might be a useful indicator of avoidable harm to patients from systemic anticancer treatments, but data for this indicator are limited. The Systemic Anti-Cancer Therapy (SACT) dataset collated by Public Health England allows the assessment of factors affecting 30-day mortality in a national patient population. The aim of this first study based on the SACT dataset was to establish national 30-day mortality benchmarks for breast and lung cancer patients receiving SACT in England, and to start to identify where patient care could be improved.

Methods: In this population-based study, we included all women with breast cancer and all men and women with lung cancer residing in England, who were 24 years or older and who started a cycle of SACT in 2014 irrespective of the number of previous treatment cycles or programmes, and irrespective of their position within the disease trajectory. We calculated 30-day mortality after the most recent cycle of SACT for those patients. We did logistic regression analyses, adjusting for relevant factors, to examine whether patient, tumour, or treatment-related factors were associated with the risk of 30-day mortality. For each cancer type and intent, we calculated 30-day mortality rates and patient volume at the hospital trust level, and contrasted these in a funnel plot.

Findings: Between Jan 1, and Dec, 31, 2014, we included 23 228 patients with breast cancer and 9634 patients with non-small cell lung cancer (NSCLC) in our regression and trust-level analyses. 30-day mortality increased with age for both patients with breast cancer and patients with NSCLC treated with curative intent, and decreased with age for patients receiving palliative SACT (breast curative: odds ratio [OR] 1·085, 99% CI 1·040-1·132; p<0·0001; NSCLC curative: 1·045, 1·013-1·079; p=0·00033; breast palliative: 0·987, 0·977-0·996; p=0·00034; NSCLC palliative: 0·987, 0·976-0·998; p=0·0015). 30-day mortality was also significantly higher for patients receiving their first reported curative or palliative SACT versus those who received SACT previously (breast palliative: OR 2·326 99% CI 1·634-3·312; p<0·0001; NSCLC curative: 3·371, 1·554-7·316; p<0·0001; NSCLC palliative: 2·667, 2·109-3·373; p<0·0001), and for patients with worse general wellbeing (performance status 2-4) versus those who were generally well (breast curative: 6·057, 1·333-27·513; p=0·0021; breast palliative: 6·241, 4·180-9·319; p<0·0001; NSCLC palliative: 3·384, 2·276-5·032; p<0·0001). We identified trusts with mortality rates in excess of the 95% control limits; this included seven for curative breast cancer, four for palliative breast cancer, five for curative NSCLC, and seven for palliative NSCLC.

Interpretation: Our findings show that several factors affect the risk of early mortality of breast and lung cancer patients in England and that some groups are at a substantially increased risk of 30-day mortality. The identification of hospitals with significantly higher 30-day mortality rates should promote review of clinical decision making in these hospitals. Furthermore, our results highlight the importance of collecting routine data beyond clinical trials to better understand the factors placing patients at higher risk of 30-day mortality, and ultimately improve clinical decision making. Our insights into the factors affecting risk of 30-day mortality will help treating clinicians and their patients predict the balance of harms and benefits associated with SACT.

Funding: Public Health England.

Figure 1

Study profile for our analyses in this report NSCLC=non-small cell lung cancer. *The number of excluded patients with NSCLC is not shown here, as the excluded patient group was not traced in the National Cancer Registration and Analysis Service for additional morphology data.

Figure 2

Funnel plot of variation in risk-adjusted 30-day mortality in patients with breast cancer given systemic anticancer therapy with curative intent, by hospital trust Each circle represents a separate hospital trust; blue and red circles represent outliers beyond the 95% and 99·8% confidence interval boundaries that are represented as grey lines. Red line shows national risk-adjusted 30-day mortality rate.

Figure 3

Funnel plot of variation in risk-adjusted 30-day mortality in patients with breast cancer given systemic anticancer therapy with palliative intent, by hospital trust Each circle represents a separate hospital trust; blue and red circles represent outliers beyond the 95% and 99·8% confidence interval boundaries that are represented as grey lines. Red line shows national risk-adjusted 30-day mortality rate.

Figure 4

Funnel plot showing variation in risk-adjusted 30-day mortality in patients with non-small cell lung cancer given systemic anticancer therapy with curative intent, by hospital trust Each circle represents a separate hospital trust; blue and red circles represent outliers beyond the 95% and 99·8% confidence interval boundaries that are represented as grey lines. Red line shows national risk-adjusted 30-day mortality rate.

Figure 5

Funnel plot showing variation in risk-adjusted 30-day mortality in patients with non-small cell lung cancer given systemic anticancer therapy with palliative intent, by hospital trust Each circle represents a separate hospital trust; blue and red circles represent outliers beyond the 95% and 99·8% confidence interval boundaries that are represented as grey lines. Red line shows national risk-adjusted 30-day mortality rate.