Original ResearchPredictors of poor serologic response to COVID-19 vaccine in patients with cancer: a systematic review and meta-analysis
Introduction
Coronavirus disease-19 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread throughout the world, afflicting more than 459.7 million people, resulting in more than 6 million deaths globally as of 16 March 2022, and with a mortality rate about 1.3%. The morbidity and mortality of COVID-19 were found higher in patients with cancer [1,2]. Worldwide, an estimated 19.3 million new cancer cases and almost 10.0 million cancer deaths occurred in 2020, and the global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020 [3]. It is precisely because that patients with cancer are purported to have poor COVID-19 outcomes [[4], [5], [6], [7]], and recent studies report that hydroxychloroquine and convalescent plasma demonstrate no efficacy against COVID-19 infection [[8], [9], [10]], disease prevention is the most effective way to contain new cases, and major medical societies fostered priority mass vaccination in this high-risk population [11,12].
For this reason, healthcare authorities should prioritise vaccinations for patients with cancer. On the basis of the clinical trials [13], considering the high morbidity and mortality from COVID-19 in patients with cancer, the benefits of vaccination are likely to far outweigh the risks of vaccine-related adverse events. However, researches [[14], [15], [16], [17]] demonstrate a lower probability to obtain seroconversion after a complete course of COVID-19 vaccination, with about 6% of patients with cancer in treatment failed to develop an immune response after mRNA vaccination, as compared to only 0.2% in controls, accounting for a 30-fold higher probability [14].
Patients with cancer have an impaired immune response to COVID-19 vaccination with lower and/or lagged seroconversion rate [18,19]. The vaccination against COVID in cancer (VOICE) study aimed to reveal influences of anti-cancer treatments in response to vaccination [20], and the COVID-19 antiviral response (CAPTURE), a pan-tumour immune monitoring study, suggested a fundamental understanding of the interaction between host immunity, the virus, cancer, and anti-cancer treatments placed in the wider healthcare context in order to minimise harm and optimise cancer outcomes [21]. To propose a tailored approach to COVID-19 vaccination for patients with cancer, a thorough understanding of factors affecting on COVID-19 vaccination efficacy in patients with cancer with poor immune conditions is requisite. We conducted this meta-analysis to assess the factors that predict poor seroconversion comprehensively in order to plan better prevention strategies in this frail population.
Section snippets
Methods
We did a systematic review and meta-analysis of studies on factors affecting humoural response to COVID-19 vaccine in patients with cancer. The review was registered with PROSPERO (CRD42022315687) and reported according to PRISMA guidelines [22].
Characteristics of studies
Out of a total of 68 abstracts were screened, 22 were retrieved for more detailed evaluation. The two excluded studies lacked sufficient data (shown in Fig. 1). Finally, 20 cohort studies met the inclusion criteria for this study [14,16,[27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44]], with 5,499 patients with cancer. All of which used a historical cohort design, with seven countries were represented. Of all the studies, one in the
Discussion
This systematic review summarises the available global data of the effects of predictors on poor serologic response to COVID-19 vaccine in patients with cancer during the COVID-19 pandemic. We found that advanced age, male patients, and metastatic disease increased negative seroconversion to COVID-19 vaccine. IGHV mutated status, high concentration of Ig G, Ig M, and Ig A were correlated with seropositivity in patients with haematologic malignancies. Relating to cancer treatment strategy,
Funding
The present study received no funding support.
Author contribution
Kui Zhang contributes to the Conceptualisation; Wenxing Yang and Dongxue Zhang contribute to Data curation and Project administration; Zhuo Li contributes to Software and Writing - review and editing; Wenxing Yang and Kui Zhang contribute to Writing - original draft.
Conflict of interest statement
No conflicts of interests to declare.
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These authors contributed equally to this work.