Abstract
Objective
Recent advancements highlight promising outcomes with immune checkpoint inhibitors (ICIs) when combined with concurrent chemoradiotherapy (CCRT) or chemotherapy in the treatment of locally advanced cervical cancer (LACC). This systematic review and meta-analysis aimed to assess the efficacy and safety of ICIs combined with CCRT/chemotherapy in patients with LACC.
Methods
We searched PubMed, Embase, Cochrane and ClinicalTrials.gov for randomized controlled trials (RCTs) and non-RCTs assessing the efficacy and safety of ICIs plus CCRT/chemotherapy in patients with LACC. All analyses were performed in R software (v.4.4.0).
Results
Our systematic review and meta-analysis included 3 RCTs and 4 observational studies, corresponding to 1,250 patients. The 1-year progression-free survival (PFS) was 78% (95% confidence interval [CI]=75–80, I2=0%), while the 1-year overall survival (OS) reached 93% (95% CI=89–95, I2=50%). The objective response rates were 88% (95% CI=74–95, I2=74%). We performed a comparative analysis of PFS and OS using data from the 2 RCTs. The results indicated that the ICI plus CCRT group had a significantly lower risk of disease progression or death compared to the CCRT group alone (PFS: hazard ratio [HR]=0.76, 95% CI=0.64–0.91, I2=4%; OS: HR=0.76, 95% CI=0.58–0.98, I2=0%), representing an approximate 25% reduction in risk. The analysis of grade ≥3 adverse events revealed the low incidences, with none exceeding 15%.
Conclusion
Our findings suggest that ICIs are effective and safe to use with CCRT/chemotherapy in LACC patients. Further RCTs are needed to confirm these findings.
Trial Registration
International Prospective Register of Systematic Reviews Identifier: CRD42024576145
Keywords: Immune Checkpoint Inhibitors, Cervical Cancer, Progression-Free Survival, Meta-Analysis
Synopsis
This study evaluates the efficacy and safety of combining immune checkpoint inhibitors with concurrent chemoradiotherapy/chemotherapy in locally advanced cervical cancer. It shows promising survival outcomes and reduced disease progression risk. The treatment is well-tolerated with fewer severe adverse events. However, further research is needed.
INTRODUCTION
Cervical cancer is the fourth most common cancer and the fourth leading cause of cancer-related deaths in women worldwide [1]. The incidence and mortality rate is particularly high in Asian population, with 290,190 new cases diagnosed and 143,410 deaths reported in 2019. This burden is especially concerning in the lower-middle income countries where healthcare resources are limited [2]. Although early diagnosis and the introduction of the human papillomavirus (HPV) vaccine have significantly reduced the incidence of cervical cancer worldwide, survival rates remain largely unchanged after cancer development with approximately 35% of newly diagnosed cases being locally advanced at presentation [3].
The definition of locally advanced cervical cancer (LACC) has evolved with various editions of International Federation of Gynaecology and Obstetrics/Fédération Internationale de Gynécologie et d’Obstétrique (FIGO) staging system. While in the 2009 and 2014 editions, LACC included stages IB2 to IVA; this subgroup of patients is included in stages IB3–IVA as per the FIGO 2018 version [4,5,6]. Unsurprisingly, when compared to early-stage cervical cancer, LACC is associated with significantly lower cure rates, with 5-year disease-free survival and overall survival (OS) rates of 68% and 74%, respectively. Poorer outcomes are particularly associated with advancing disease stages and lymph node involvement [7].
For nearly 2 decades, concurrent chemoradiotherapy (CCRT) involving platinum-based chemotherapy along with external beam radiotherapy (EBRT), followed sometimes by brachytherapy, has been the standard treatment for LACC [8]. However, as the disease progresses to higher stages (stage ≥III), the efficacy of CCRT tends to diminish [8]. Some centers advocate neoadjuvant chemotherapy followed by radical surgery, but the recurrence rate with available therapeutic approaches remains high [9], highlighting the need for alternative therapeutic options. Recently, the combination of immune checkpoint inhibitors (ICIs) with CCRT has emerged as a promising treatment strategy.
Two randomized controlled trials (RCTs) by Lorusso et al. [10] and Monk et al. [11] (Keynote-A18 and CALLA trials, respectively) have explored the efficacy of adding ICIs to CCRT in LACC, both reporting encouraging results compared to CCRT alone. In addition, Li et al. [12] conducted a phase 2 trial investigating camrelizumab, (an ICI) combined with neoadjuvant chemotherapy followed by surgery, further supporting the potential benefit of incorporating immunotherapy in this setting. A recent meta-analysis by Zhao et al. [13] pooled survival outcomes from these 2 RCTs and reported favorable progression-free survival (PFS) and OS. However, this analysis was limited by the inclusion of only 2 RCTs, resulting in insufficient statistical power for a robust conclusion. Other published meta-analyses have often included patients with metastatic or recurrent cervical cancer alongside those with LACC [14,15], limiting the applicability of the findings to the LACC population specifically. As a result, there remains a lack of comprehensive evidence focusing exclusively on LACC, making it challenging to inform or possibly change the current standard of care. Therefore, we conducted a systematic review and single-arm meta-analysis, including both RCTs and non-RCTs, to increase the sample size and provide a more robust and comprehensive evaluation of the efficacy and safety of ICIs combined with CCRT/chemotherapy in patients with LACC.
MATERIALS AND METHODS
This systematic review and meta-analysis were conducted in accordance with the recommendations of Cochrane Handbook for Systematic Reviews and Interventions [16] and the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) [17] checklist (Table S1). The prospective meta-analysis protocol was registered with the International Prospective Register of Systematic Reviews registry under the protocol number (PROSPERO; CRD42024576145).
1. Search strategy and study selection
We systematically searched PubMed, Embase, Cochrane, and ClinicalTrials.gov for relevant studies published from inception to June 2024, using the terms “cervical cancer,” “chemoradiotherapy,” and “immune checkpoint inhibitors.” The search strategy also included appropriate MeSH and Emtree terms. The full search strategy is detailed in Table S2. Two authors (P.I.J. and R.I.J.) independently screened the retrieved literature using Rayyan [18] following predefined inclusion and exclusion criteria. Any discrepancies were resolved through a panel discussion with a third author (S.V.).
2. Selection criteria
1) Type of studies: We included RCTs and non-RCTs that assessed the efficacy and safety of ICIs combined with chemoradiotherapy/chemotherapy in LACC patients. Due to the limited number of RCTs, non-RCTs were included to enhance sample size and strengthen the evidence base. Studies such as case reports, case series, reviews, meta-analyses, conference abstracts and animal studies were excluded.
2) Population: The analysis focused on treatment-naive LACC patients undergoing curative treatment. LACC was defined according to the FIGO staging system (2009, 2014, or 2018) as reported in the included studies [4,5,6]. We excluded studies with overlapping populations and studies with patients having recurrent/metastatic cervical cancer, concomitant non-cervical primary or patients who were unable to get chemotherapy or radiation or immunotherapy.
3) Intervention: Studies were included if they assessed the administration of ICIs, either concomitantly with or sequentially following CCRT or chemotherapy, irrespective of the treatment setting.
4) Control: As this is a single-arm meta-analysis, studies without a control group were also included. In cases where control groups were present, they consisted of a placebo and/or standard CCRT or chemotherapy.
5) Outcomes: We included studies that reported any of the following endpoints: (a) 1-year PFS; (b) 1-year OS; (c) objective response rate (ORR), comprising patients with complete and partial response; (d) disease control rate (DCR), comprising patients with complete response, partial response and stable disease; (e) progressive disease (PD); (f) grade ≥3 adverse events according to Common Terminology Criteria for Adverse Events (CTCAE) version 4 or 5 [19,20].
3. Data extraction and quality assessment
Two independent authors (P.I.J. and R.I.J.) extracted relevant data from the included studies. The quality of RCTs was assessed using the Cochrane Risk of Bias (RoB 2) [21] tool, and the quality of non-randomized studies was evaluated with the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool [22]. Two investigators (P.I.J. and R.I.J.) individually conducted the quality assessment. Disagreements during data extraction or quality evaluation were resolved through discussion and consensus among authors.
4. Statistical analyses
A single-arm proportional meta-analysis was performed to evaluate the efficacy and safety of ICIs with CCRT/chemotherapy in LACC patients. All statistical analyses were conducted using R software (version 4.4.0, R Core team 2024; R Foundation for Statistical Computing, Vienna, Austria) [23] and associated R packages. Logit proportion was used for the outcomes with individual study proportions <0.2 or >0.8, and Double Arcsine proportion for those with individual study proportions of 0 or 1. A random-effects model was employed for all outcomes to account for potential heterogeneity across the included studies. Comparative meta-analyses including the 2 RCTs were also performed for the primary outcomes, PFS and OS using hazard ratio (HR) with 95% confidence interval (CI). Subgroup analysis of PFS of the 2 RCTs was done based on FIGO stage. Post hoc subgroup analyses were done based on the type of ICI used and treatment setting to investigate whether any subgroup shows greater efficacy. This was done to generate hypotheses about the most appropriate ICI type and treatment setting for patients with LACC. The subgroup analyses were also used to explore the heterogeneity of primary endpoints.
We assessed heterogeneity across studies using the Cochrane Q test and the I2 statistic. A p-value <0.1 for the Q test and an I2 >30% were considered indicative of significant heterogeneity. To address heterogeneity in efficacy outcomes, leave-one-out sensitivity analyses were performed. Publication bias was evaluated through the visual inspection of funnel plots.
RESULTS
1. Study triage and baseline characteristics
Our systematic search yielded 1,324 results. After deduplication and title/abstract exclusion, 68 studies were fully assessed. Ultimately, 7 studies matched the inclusion criteria and were included in our analyses, including 3 RCTs [10,11,12,24,25,26,27]. Although the study by Duska et al. [24] is an RCT, its control group did not meet the inclusion criteria; therefore, patient characteristics from the intervention group alone were extracted. Comprehensive details of the study selection are detailed in Fig. 1.
Fig. 1. Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) flow chart for study triage.
The characteristics of the included studies are summarized in Table 1. A total of 2,050 patients were analyzed, comprising 1,104 patients in the ICI group and 946 in the control group. The median age of the participants ranged from 47 to 55 years, with 1,576 (77%) presenting with regional lymph node positivity. The median follow-up period varied from 4.6 to 23.8 months.
Table 1. Baseline characteristics of included studies.
| Study | Study design | Intervention | Control | Median follow-up (mo) | No. of patients (ICI/Control) | Median age (yr; ICI/Control) | Race/ethnicity | FIGO stage | Regional lymph node positive | Histology (squamous) | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ICI | Control | ICI | Control | ICI | Control | ICI | Control | |||||||
| Duska et al., 2020 [24] | RCT | Pembrolizumab with CCRT | Pembrolizumab following CCRT* | 4.6 | 28/NA | NA/NA | White: 22 (78.5) | NA | IB1†: 3 (11) | NA | 16 (57) | NA | 24 (86) | NA |
| Asian: NA | IB2–IIB: 17 (61) | |||||||||||||
| Others: 6 (22.5) | III–IVA: 8 (28) | |||||||||||||
| Li et al., 2023 [12] | Non-RCT | Camrelizumab with neoadjuvant chemotherapy‡ | No control group | 11 | 85/NA | 51/NA | Asian§: 85 (100) | NA | IB3–IIB: 67 (79) | NA | 18 (21) | NA | 82 (96) | NA |
| IIIC1: 18 (21) | ||||||||||||||
| Liu et al., 2023 [27] | Non-RCT | Camrelizumab/sintilimab with and following CCRT | CCRT | 14 | 29/30 | 56∥/55∥ | Asian§:29 (100) | Asian§:30 (100) | IIB: 4 (14) | IIB: 3 (10) | 29 (100) | 30 (100) | 28 (97) | 29 (97) |
| III–IVA: 25 (86) | III–IVA: 27 (90) | |||||||||||||
| Lorusso et al., 2024 [10] | RCT | Pembrolizumab with and following CCRT | Placebo with and following CCRT | 17.9 | 529/531 | 49/50 | White: 254 (48) | White: 264 (50) | IB2–IIB: 235 (44) | IB2–IIB: 227 (43) | 445 (85) | 438 (83) | 433 (82) | 451 (85) |
| Asian: 155 (29) | Asian: 148 (28) | III–IVA: 294 (56) | III–IVA: 304 (57) | |||||||||||
| Others: 120 (23) | Others: 119 (22) | |||||||||||||
| Mayadev et al., 2020¶ [25] | Non-RCT | Ipilimumab following CCRT | No control group | 14.8 | 32/NA | 50/NA | White: 22 (69) | NA | IB2–IIB: 24 (75) | NA | 30 (94) | NA | 28 (88) | NA |
| Asian: 2 (6) | IIIB–IVA: 8 (25) | |||||||||||||
| Others: 8 (25) | ||||||||||||||
| Monk et al., 2023 [11] | RCT | Durvalumab with and following CCRT | Placebo with and following CCRT | 18.5 | 385/385 | 50/48 | White: 130 (34) | White: 125 (33) | IB2–IIB: 135 (36) | IB2–IIB: 130(33) | 279 (73) | 291 (76) | 322 (84) | 320 (83) |
| Asian: 152 (40) | Asian: 148 (38) | III–IVA: 250 (64) | III–IVA: 255 (67) | |||||||||||
| Others: 103 (26) | Others: 112 (29) | |||||||||||||
| Rodrigues et al., 2023 [26] | Non-RCT | Nivolumab with and following CCRT | No control group | 23.8 | 16/NA | 47/NA | NA | NA | IB3–IIB: 10 (63) | NA | NA | NA | 14 (87.5) | NA |
| IIIB–IVA: 6 (37) | ||||||||||||||
Values are presented as number (%).
CCRT, concurrent chemoradiotherapy; FIGO, International Federation of Gynaecology and Obstetrics; ICI, immune checkpoint inhibitor; NA, not available; RCT, randomized controlled trial.
*The control group doesn’t meet inclusion criteria, that’s why its data are not included in the table.
†IB1 with positive nodes fall under locally advanced cervical cancer (according to FIGO stage 2018).
‡Data was extracted from the study before the patients underwent surgery.
§Race was not explicitly provided in these studies, but considering that the studies were conducted in Chinese hospitals, all patients included in the studies were considered of Asian ethnicity.
∥Mean.
¶Data for intention to treat population (n=32) are extracted.
2. Treatment modalities
Most of the analyzed studies employed 5 or 6 cycles of cisplatin (40 mg/m2) plus EBRT once weekly, followed by brachytherapy. The EBRT dose ranged between 45–50 Gray (Gy), while the brachytherapy dose varied from 25–40 Gy. Notably, Li et al. [12] utilized a neoadjuvant chemotherapy regimen consisting of nab-paclitaxel and cisplatin, followed by radical surgery.
3. Efficacy outcomes
The pooled analysis showed a 1-year PFS of 78% (95% CI=75–80, I2=0%; Fig. 2A) with no significant heterogeneity among studies. The 1-year OS rate was 93% (95% CI=89–95, I2=50%; Fig. 2B), Other outcomes included an ORR of 88% (95% CI=74–95, I2=74%; Fig. 2C), DCR of 89% (95% CI=77–95, I2=78%; Fig. 2D), and a PD rate of 6% (95% CI=1–14, I2=83%; Fig. 2E), all exhibiting significant heterogeneity among studies.
Fig. 2. The forest plots show the prevalence of 1-year PFS (A), the prevalence of 1-year OS (B), the prevalence of ORR (C), the prevalence of DCR (D) and the prevalence of PD (E). The prevalence of 1-year PFS was 78% (95% CI=75%–80%, I2=0%). The prevalence of 1-year OS was 93% (95% CI=89%–95%, I2=50%). The prevalence of ORR was 88% (95% CI=74%–95%, I2=74%). The prevalence of DCR was 89% (95% CI=77%–95%, I2=78%). The prevalence of PD was 6% (95% CI=1%–14%, I2=83%).
CI, confidence interval; DCR, disease control rate; IV, inverse variance; OS, overall survival; ORR, objective response rate; PD, progressive disease; PFS, progression-free survival.
*Data was extracted from Kaplan-Meier curve.
Comparative analyses for PFS (HR=0.76, 95% CI=0.64–0.91, p< 0.01, I2=4%; Fig. 3A) and OS (HR=0.76, 95% CI=0.58–0.98, p=0.04, I2=0%; Fig. 3B) including the 2 RCTs, demonstrated approximately a 25% lower risk of disease progression or death in the ICI group compared to the control group. A subgroup analysis of PFS, based on FIGO stages IB2–IIB and III–IVA, was conducted using data from the 2 RCTs to explore whether ICIs were more effective in higher stages of disease. The pooled HR for PFS was 0.89 (95% CI=0.67–1.19, p=0.45, I2=0%; Fig. S1) for FIGO stage IB2–IIB and 0.73 (95% CI=0.52–1.01, p=0.06, I2=52%; Fig. S1) for FIGO stage III–IVA. No significant differences were observed between these subgroups (p=0.36).
Fig. 3. The forest plots show the exploratory analysis of randomized controlled trials pooling the outcomes of PFS (A) and OS (B). The HR of PFS was 0.76 (95% CI=0.64–0.91; I2=4%). The HR of OS was 0.76 (95% CI=0.58–0.98).
CI, confidence interval; HR, hazard ratio; ICI, immune checkpoint inhibitor; IV, inverse variance; OS, overall survival; PFS, progression-free survival.
Subgroup analyses based on different types of ICI used, namely anti-cytotoxic T lymphocyte antigen 4 (CTLA4), anti-programmed cell death 1 (PD1) and anti-programmed cell death-ligand 1 (PDL1), across the included studies did not show significant efficacy among different subgroups (Fig. S2). Post hoc subgroup analyses were also done based on the treatment setting, although PFS and OS didn’t show any significant result, ORR, DCR and PD were consistently better with neoadjuvant ICI use (Fig. S3). However, since only one study was included in that subgroup, the results must be interpreted with caution.
To investigate the heterogeneity observed in the efficacy outcomes, leave-one-out sensitivity analyses were performed (Fig. S4). However, these analyses did not fully explain the heterogeneity, which could be attributed to variations in study design and the types of ICIs used. Although subgroup analyses based on type of ICI used didn’t explain the heterogeneity observed, treatment setting was a key source of heterogeneity in case of ORR, DCR and PD (Fig. S3).
4. Safety outcomes
A summary table of pooled safety outcomes is shown in Table 2 which categories the adverse events according to type and grade. The pooled analysis of adverse events of any grade across the included studies showed the highest frequency for nausea (60%, 95% CI=35–83), followed by anemia (53%, 95% CI=38–67) and diarrhoea (44%, 95% CI=20–70).On the other hand, in case of grade ≥3 adverse events, decreased neutrophil count had the highest frequency (13%, 95% CI=5–25), followed by anemia (10%, 95% CI=4–17) and hypokalemia(4%, 95% CI=2–8).
Table 2. Summary table of pooled adverse events.
| Type of adverse events | Any grade | Grade ≥3 | |||
|---|---|---|---|---|---|
| No. of studies | Proportion (95% CI) | No. of studies | Proportion (95% CI) | ||
| Blood/lymphatics | |||||
| Anemia | 5 | 52.92 (38.19–67.17) | 7 | 9.71 (4.28–16.72) | |
| Gastrointestinal | |||||
| Nausea | 5 | 60.00 (34.78–82.78) | 7 | 0.35 (0.01–1.02) | |
| Vomiting | 4 | 28.63 (20.32–36.93) | 6 | 0.02 (0.00–0.39) | |
| Diarrhoea | 4 | 43.92 (19.60–69.82) | 5 | 1.86 (0.35–4.11) | |
| Endocrine | |||||
| Hypothyroidism | 3 | 13.01 (5.34–22.97) | 4 | 0.00 (0.00–0.31) | |
| Hyperthyroidism | 3 | 8.98 (4.17–15.15) | 4 | 0.00 (0.00–0.21) | |
| Metabolic | |||||
| Hypokalemia | 4 | 11.78 (5.20–20.33) | 5 | 4.11 (1.97–8.39) | |
| Infection | |||||
| Urinary tract infection | 3 | 22.55 (3.59–50.32) | 5 | 0.75 (0.00–2.46) | |
| Investigations | |||||
| Neutrophil count decreased | 3 | 42.29 (7.09–82.68) | 5 | 13.05 (4.51–24.62) | |
| Platelet count decreased | 4 | 32.09 (11.03–57.66) | 6 | 2.59 (0.91–4.84) | |
| Increased ALT | 3 | 14.81 (1.87–35.42) | 3 | 0.05 (0.00–2.93) | |
| Increased AST | 3 | 16.26 (2.22–38.17) | 4 | 0.01 (0.00–1.93) | |
ALT, alanine aminotransferases; AST, aspartate aminotransferases; CI, confidence interval.
5. Quality assessment
Risk of bias assessments were conducted for 3 RCTs and 4 non-RCTs. Among the non-randomized studies, all demonstrated a moderate risk of bias. The RCTs consistently exhibited a low risk of bias (Figs. S5 and S6). Upon visual inspection of the funnel plots for 1-year PFS and 1-year OS, the studies appeared symmetrically distributed around the central axis, suggesting minimal publication bias (Fig. S7). However, one study demonstrated asymmetry in the funnel plot for 1-year PFS, likely attributable to its small sample size [27].
DISCUSSION
This systematic review and meta-analysis, encompassing 7 studies and 2,050 patients, assessed the efficacy and safety of ICI in combination with CCRT/chemotherapy in patients with LACC. Our main findings were as follows:1) 1-year PFS of 78%, 2) 1-year OS of 93%, and 3) ORR of 88% in patients receiving ICI in addition to CCRT/chemotherapy. Notably, an exploratory analysis of the 2 available RCTs demonstrated nearly a 25% reduction in the risk of disease progression or death among LACC patients receiving ICIs compared to CCRT/chemotherapy. Moreover, the overall incidence of clinically significant grade 3 or higher adverse events was lower, with no individual event exceeding 15%, while the incidence of any grade adverse events didn’t exceed 60%.
While CCRT has remained the standard care of treatment for LACC for over 2 decades, considering the broad range of diseases, with their varied prognosis that fall under the umbrella term, a uniform treatment strategy may not be appropriate for all cases [9]. There is an increasing need to redefine the broad classification of LACC and tailor treatment strategies based on specific risk factors, such as tumor grading, histological subtype, lymphovascular space invasion and HPV subtype [9]. While conducting this systematic review and meta-analysis, we recognized the need for larger RCTs based on this concept.
Immunotherapy has emerged as one of the most promising treatment approaches in oncology, with cervical cancer being a key area of interest [28]. Its use is supported by the interplay between the immune system, HPV infection and cervical cancer progression [7]. Approximately 20% of cervical cancer cases exhibit a high tumor mutation burden, indicating the presence of tumor-specific antigens [7]. Furthermore, elevated expression of immune checkpoints, such as CTLA4 and PD1/PDL1, has been observed in both intraepithelial lesions and cervical cancer, providing a strong biological rationale for exploring immunotherapy in this setting [29]. These findings have laid the foundation for numerous studies evaluating the efficacy of immunotherapeutic agents in cervical cancer management.
Several studies have evaluated the efficacy of ICI monotherapy in cervical cancer. However, the results have been largely unsatisfactory [28]. Recently, 2 pivotal phase 3 RCTs investigated the combination of ICIs with CCRT. The Keynote-A18 trial, conducted by Lorusso et al. [10], assessed pembrolizumab with CCRT, leveraging the hypothesis that ICIs’ immune-stimulatory effects could enhance the efficacy of chemoradiotherapy [30]. Similarly, the CALLA trial, conducted by Monk et al. [11], examined the combination of durvalumab with CCRT. Interestingly, a key difference emerged in the PFS outcomes between these trials. While Keynote-A18 demonstrated a statistically significant improvement in 2-year PFS (68% in the treatment arm vs. 57% in the control arm; HR=0.70, 95% CI=0.55–0.89), the CALLA trial did not observe a significant PFS benefit (HR=0.84, 95% CI=0.65–1.08).
The discrepancy in results may be attributed to differences in inclusion criteria, particularly regarding the number and size of positive lymph nodes, as well as the type of ICI used [10,31]. The Keynote-A18 trial included patients at a higher risk of progression or death than those in the CALLA trial, potentially explaining the greater observed treatment benefit [10]. This suggests that adding ICIs to CCRT may yield better outcomes in patients with more advanced stages of disease. To explore this hypothesis, we performed a subgroup analysis of PFS in FIGO stages IB–IIB vs. III–IVA, pooling data from both RCTs. However, no statistically significant differences in ICI efficacy were observed across these subgroups. Given that this analysis was exploratory and limited to 2 RCTs, further trials stratified on the basis of FIGO stages are necessary to validate these findings. Subgroup analyses of efficacy outcomes based on different types of ICI also didn’t show any significant results, which may be attributed to the smaller number of studies in each subgroup.
On another note, Xiang et al. [32] showed that the 2-year PFS rate was statistically significant in Asian populations of Keynote-A18 (HR=0.55, 95% CI=0.35–0.88). This finding puts forward the hypothesis that Asians are sensitive to ICI therapy. However, Monk et al. [11] didn’t show any significant benefit of ICI therapy based on Asian ethnicity. Thus, whether Asians are sensitive to ICI therapy or particularly to pembrolizumab remains yet to be seen and requires further investigation through well-designed RCTs to validate the hypothesis.
Beyond the discussed RCTs, several phase 1 and phase 2 trials have evaluated the combination of ICI with CCRT in LACC patients, showing favorable results [24,26]. Among these, the study by Mayadev et al. [25] was unique in using ipilimumab, a CTLA4 inhibitor, following CCRT. While this phase 1 trial yielded encouraging findings, further research is needed to determine whether anti-CTLA4 therapies are more effective than anti-PD1/PDL1 therapies in this context. Another notable study included in our analysis was by Li et al. [12], which utilized neoadjuvant chemotherapy combined with camrelizumab. Although CCRT remains the standard of care for LACC, the rationale for using neoadjuvant chemotherapy lies in its comparable OS outcomes and potentially lower long-term complication rates [11]. Though the study showed promising results, additional trials are necessary to confirm its efficacy. In our post-hoc subgroup analyses, treatment done in neoadjuvant setting showed improved efficacy. However, this result must be interpreted with utmost caution due to the post hoc nature of the subgroup and inclusion of only one study in that specific subgroup.
A recent meta-analysis by Zhao et al. [13] combined PFS and OS outcomes from the Keynote-A18 and CALLA trials, and their results align with our exploratory analysis of these 2 RCTs. However, a major limitation of their study was the inclusion of only 3 studies [13]. To address this, our analysis incorporated phase 1 and phase 2 studies, expanding the sample size and providing a more comprehensive perspective. Several ongoing trials, e.g., the ATOMICC and ATEZOLACC trials investigating the efficacy of dostarlimab and atezolizumab, respectively, will offer further insights into optimizing treatment strategies for LACC patients [33,34].
Synergistic therapeutic approaches like vaccine, adoptive T cell therapy, etc. are being investigated for recurrent or advanced cervical cancer with promising outcomes [35,36,37]. To the authors’ best knowledge, these approaches are still investigational in patients with LACC, and their efficacy in this group remains to be established.
This study has certain limitations. As a relatively new area with limited published literature, we included early-phase trials (phases 1 and 2) to better assess ICI safety. Consequently, the included studies lacked mature data. Long-term outcomes like prolonged PFS, OS and quality-of-life measures were unavailable, highlighting the need for more mature data. Our analysis showed substantial heterogeneity. This likely stems from the single-arm meta-analysis design, variations in treatment sequences/protocols, and differences in individual treatment modalities. Comparative analyses of PFS and OS relied on only 2 RCTs. These conclusions should therefore be interpreted cautiously. We acknowledge that with insufficient data on potential biomarkers, the scope of personalized treatment recommendations with these results is limited. The optimal chemoradiotherapy dosing and fraction schedule to combine with ICIs remains undetermined due to significant variability across the included studies’ treatment regimens. Subgroup analyses were post hoc and included fewer studies in each subgroup. These analyses are consequently underpowered and must be interpreted cautiously.
Despite its limitations, this remains to the authors’ knowledge the most detailed meta-analysis on this subset of patients, comprehensively including all relevant patient data, enabling creation of robust evidence base to establish safety and potential survival benefit. Our work identifies various factors (like stage stratification, lymph node status, etc.) that can be used to plan the protocol for a multi-centre RCT that might adequately answer the position of ICIs in the treatment landscape of cervical cancer.
This meta-analysis demonstrated that ICIs can be safely combined with CCRT/chemotherapy for treatment of LACC, and for a subset of patients can reduce risk of disease progression or death by approximately 25%. Larger RCTs are needed to confirm these findings.We anticipate that ongoing research may further establish the role of ICIs in routine patient care.
ACKNOWLEDGEMENTS
We thank Beatriz Araújo for her help with proofreading.
Footnotes
Conflict of Interest: No potential conflict of interest relevant to this article was reported.
- Conceptualization: P.I.J.
- Data curation: P.I.J., R.I.J.
- Formal analysis: P.I.J., R.I.J.
- Investigation: P.I.J., R.I.J.
- Methodology: P.I.J., R.I.J.
- Software: P.I.J., R.I.J.
- Supervision: S.V.
- Validation: S.V.
- Visualization: P.I.J.
- Writing - original draft: P.I.J.
- Writing - review & editing: P.I.J., S.V.
SUPPLEMENTARY MATERIALS
Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2020 checklist
Search strategy for all the registers
The forest plot shows the subgroup analysis of PFS based on FIGO stage IB2–IIB vs. III–IVA. The pooled HR of PFS in FIGO stage IB2–IIB was 0.89 (95% CI=0.67–1.19, p=0.45, I2=0%) and in FIGO stage III–IVA was 0.73 (95% CI=0.52–1.01, p=0.06, I2=52%). There was no subgroup difference found between these 2 stages (p=0.36).
The forest plots show the subgroup analyses of efficacy outcomes. (A) One-year PFS, (B) 1-year OS, (C) ORR, (D) DCR, and (E) PD based on the type of ICI used. The subgroup analyses didn’t show any significant results.
The forest plots show the subgroup analyses of efficacy outcomes. (A) One-year PFS, (B) 1-year OS, (C) ORR, (D) DCR, and (E) PD based on treatment setting. The subgroup analyses demonstrated increased efficacy in the neoadjuvant setting in case of ORR, DCR and PD.
The forest plots show the leave-one-out sensitivity analysis done for the efficacy outcomes that showed high heterogeneity: (A) 1-year OS, (B) ORR, (C) DCR and (D) PD.
Risk of bias summary for non-randomized studies (Risk of Bias in Non-Randomized Studies of Interventions [ROBINS-I]).
Risk of bias summary for randomized study (Risk of Bias Assessment Tool for Randomized Trial [RoB 2]).
Funnel plots for assessing publication bias in (A) 1-year PFS and (B) 1-year OS. Visual inspection of the funnel plot of 1-year PFS and 1-year OS shows a mostly symmetrical pattern of studies on each side and around the central axis. One study was found to be asymmetric in the funnel plot of 1-year PFS, which may be due to the small sample size.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2020 checklist
Search strategy for all the registers
The forest plot shows the subgroup analysis of PFS based on FIGO stage IB2–IIB vs. III–IVA. The pooled HR of PFS in FIGO stage IB2–IIB was 0.89 (95% CI=0.67–1.19, p=0.45, I2=0%) and in FIGO stage III–IVA was 0.73 (95% CI=0.52–1.01, p=0.06, I2=52%). There was no subgroup difference found between these 2 stages (p=0.36).
The forest plots show the subgroup analyses of efficacy outcomes. (A) One-year PFS, (B) 1-year OS, (C) ORR, (D) DCR, and (E) PD based on the type of ICI used. The subgroup analyses didn’t show any significant results.
The forest plots show the subgroup analyses of efficacy outcomes. (A) One-year PFS, (B) 1-year OS, (C) ORR, (D) DCR, and (E) PD based on treatment setting. The subgroup analyses demonstrated increased efficacy in the neoadjuvant setting in case of ORR, DCR and PD.
The forest plots show the leave-one-out sensitivity analysis done for the efficacy outcomes that showed high heterogeneity: (A) 1-year OS, (B) ORR, (C) DCR and (D) PD.
Risk of bias summary for non-randomized studies (Risk of Bias in Non-Randomized Studies of Interventions [ROBINS-I]).
Risk of bias summary for randomized study (Risk of Bias Assessment Tool for Randomized Trial [RoB 2]).
Funnel plots for assessing publication bias in (A) 1-year PFS and (B) 1-year OS. Visual inspection of the funnel plot of 1-year PFS and 1-year OS shows a mostly symmetrical pattern of studies on each side and around the central axis. One study was found to be asymmetric in the funnel plot of 1-year PFS, which may be due to the small sample size.