Skip to main content

An integrated model for prognosis in vulvar squamous cell carcinoma



Vulvar squamous cell carcinoma (VSCC) is a relatively rare gynecologic cancer. Unlike cervical squamous cell carcinoma (CSCC), in which nearly all cases are caused by HPV infection, most VSCCs are HPV-independent. Patients with VSCC also have worse overall survival (OS) than those with CSCC. Unlike CSCC, the risk factors of VSCC have not been extensively studied. Here, we investigated the prognostic values of clinicopathological parameters as well as biomarkers in patients with VSCC.


In total, 69 cases of VSCC accessions were selected for analysis between April 2010 and October 2020. The risk factors of VSCC were screened using Cox models to establish nomograms for predicting survival outcomes.


Following the multivariate COX model for OS, independent predictors including advanced age (hazard ratio [HR] 5.899, p = 0.009), HPV positivity (HR 0.092, p = 0.016), high Ki-67 index (HR 7.899, p = 0.006), PD-L1-positivity (HR 4.736, p = 0.077), and CD8 + tumor-infiltrating lymphocytes (TILs) (HR 0.214, p = 0.024) were included in the nomogram for OS; multivariate COX model for progression-free survival (PFS) was used to screen prognostic factors including advanced age (HR 2.902, p = 0.058), lymph node metastasis (HR 5.038, p = 0.056), HPV positivity (HR 0.116, p = 0.011), high Ki-67 index (HR 3.680, p = 0.042), PD-L1-positivity (HR 5.311, p = 0.045), and CD8 + TILs (HR 0.236, p = 0.014) to establish the PFS nomogram model. Based on the C-index (0.754 for OS and 0.754 for PFS) from our VSCC cohort and the corrected C-index (0.699 for OS and 0.683 for PFS) from an internal validation cohort, the nomograms demonstrated good predictive and discriminative ability. Kaplan-Meier curves also supported the excellent performance of the nomograms.


Our prognostic nomograms suggested that (1) shorter OS and PFS were associated with PD-L1-positivity, high Ki-67 index, and low CD8 + TILs; (2) HPV-independent tumors were associated with poorer survival outcome, and mutant p53 status showed no prognostic significance.

Peer Review reports


Vulvar cancer is rare, constituting 5–8% of gynecological malignancy [1]. According to the statistics of the GLOBOCAN, 45,240 new cases and 17,427 deaths from vulvar cancer were reported globally in 2020 [2]. More than 90% of vulvar cancer is squamous cell carcinoma (SCC) and usually affects post-menopausal women aged 68 or older [1, 3]. Vulvar SCC (VSCC) is classified into two types (HPV-associated and HPV-independent) based on the etiologies and their two distinct precancerous lesions, HPV-associated usual vulvar intraepithelial neoplasia (uVIN) / vulvar high-grade squamous intraepithelial lesion (HSIL) and HPV-independent differentiated vulvar intraepithelial neoplasia (dVIN) respectively [1, 4]. uVIN / HSIL is associated with infection of high-risk human papillomavirus (hrHPV) and commonly seen in younger women [3, 4], while dVIN is HPV-independent mostly arising from lichen sclerosus (LS) in older woman [3, 4]. HPV-associated VSCC shares many risk factors as cervical SCC, such as low socioeconomic status, smoking history, other sexually transmitted diseases, immunodeficiency, etc. [3, 5]. On the other hand, dVIN is the precancer of HPV-independent VSCC and has a higher risk of developing into SCC than uVIN / HSIL [6]. Furthermore, TP53 mutant status can be used to further stratify HPV-independent VSCC into two prognostic subtypes (p53 mutant and p53 wild-type) [7]. Cross-pathogenetic pathways are also possible for these two VSCC types [8].

In 2021, the International Federation of Gynecology and Obstetrics (FIGO) published a new revision to the 2009 FIGO staging of vulvar cancer based on the analysis of prospectively collected survival data on carcinoma of the vulva [9]. The 2021 vulvar cancer staging redefines depth of invasion, uses the same definition for lymph node metastases as cervical cancer, and includes cross-sectional imaging findings similar to cervical cancer [9]. However, the latest staging revision alone may not be enough, and other clinical parameters should be considered for the clinical management of vulvar cancer. For instance, due to unresectable or obvious margin positive, postoperative radiotherapy may be required depending on the distance between the tumor and vulvar midline structures (clitoris, anus, or urethra), which were not included in the current staging scheme [1].

Currently, anti-PD-1 and anti-PD-L1 inhibitors have been successfully used in the treatment of gynecological cancers including cervical and endometrial cancers [10,11,12,13]. However, by far, only limited studies investigated the expression of PD-L1 and its prognostic value in vulvar cancer [14,15,16,17]. Furthermore, the relationship among the expression of PD-L1, clinicopathological parameters, and survival of vulvar cancer remains unclear. This study aims to establish an integrated model comprising clinicopathological parameters, HPV status, and PD-L1 expression to predicate the clinical outcomes of VSCC, in hope that better risk stratification of patients could direct potentially less aggressive treatments in low-risk patients to decrease morbidity and improve quality of life.

Materials and methods

Patient samples and database

We conducted a retrospective analysis of 69 patients with VSCC between April 2010 and October 2020 at the Women’s Hospital, School of Medicine, Zhejiang University. The inclusion criteria were as follows: (1) staging surgery as the initial therapy (modified radical vulvectomy + sentinel lymph node biopsy/bilateral inguinofemoral lymphadenectomy); (2) VSCC proved by pathological diagnosis; and (3) with complete follow-up information. The exclusion criteria were: (1) combined with other tumors; (2) unknown status of lymph node metastasis (LNM); and (3) unknown HPV status. Two senior pathology physicians reviewed all the cases independently and the stage of all cases were revised according to the 2021 FIGO staging revision [1, 9].

Immunohistochemistry (IHC)

IHC was performed according to the previous studies [18,19,20]. Sections were cut at 4 µm from each paraffin block and were dried in an oven for 1 hour at 56 to 60°C. Deparaffinization, rehydration, and target retrieval were performed according to the manufacturer by fully submerging the slides in preheated (65°C) EnVision FLEX Target Retrieval Solution for antibodies, and incubating slides at 97°C for 20 minutes. Then the slides were immediately submerged in a wash buffer for 5 minutes at room temperature. With antigen retrieval, the slides were placed in the Autostainer Link 48 platform (Dako/Agilent, and subjected to FLEX peroxidase block for 5 minutes. Then, slides were incubated with primary antibodies: p16 (GM501, GeneTech, Shanghai, China), p53 (DO-7, GeneTech), Ki-67 (GM001, GeneTech), PD-L1 (22C3, Dako, Santa Clara, CA) and CD8 (C8/144B, Dako, Santa Clara, CA). Incubation time was according to primary antibody (20 to 60 minutes). After incubation with the primary antibody, incubation with the EnVision™ FLEX + Mouse LINKER anti-mouse linker antibody was performed for 30 minutes. Subsequently, all slides were rinsed in wash buffer for 5 minutes and then incubated with the EnVision™ FLEX HRP visualization reagent for 30 minutes at room temperature. After rinsing in wash buffer for 5 minutes, the enzymatic conversion of the subsequently added 3,3’-diaminobenzidine (DAB) tetrahydrochloride chromogen was performed for 10 min at room temperature followed by DAB enhancer for 5 min at room temperature.

HPV status and IHC scoring

P16 expression was graded as previously published [21]: (1) negative (score 0) when diffusely weak or absent; (2) patchy positive (score 1) when nuclear and cytoplasmic staining detected in less than 50% of tumor cells; (3) overexpressed (score 2) when diffuse nuclear positivity of tumor cells present. Tumors with scores 0 and 1 were defined as HPV-independent (p16-negative), while tumors with score 2 were defined as HPV-associated (p16-positive). Cases with discordant HPV-PCR and p16-IHC results were excluded from the study as these cases might influence the accurate subclassification of the VSCC. As previously described [17], p53 detected in > 50% of tumor nuclei or complete absence (null type) was considered as p53 mutant, while less than threshold tumor was considered as p53 wildtype. The cutoff value for Ki-67 was also 50%, where positive tumor nuclei ≤ 50% were considered Ki-67 low, and positive tumor nuclei > 50% as Ki67 high. The combined positive score (CPS) is used for the evaluation of PD-L1 expression of solid tumors [10]. CPS was calculated as the number of PD-L1-staining cells (tumor cells, lymphocytes, and macrophages) divided by the total number of viable tumor cells, multiplied by 100. Both scores ranged from 0 to 100. A cutoff score of ≥ 1 for CPS defined PD-L1 positivity. Open-source QuPath software (v0.3.2) was used to detect and annotate CD8 + tumor-infiltrating lymphocytes (TILs) [22]. CD8 + TILs density was calculated as total CD8 + cells divided by the area (mm2) comprising the tumor and areas in direct contact with the tumor periphery (within one 20x field from the tumor nest edge). Based on the median cell number (20.0 cells/mm2), VSCC cases were divided into CD8 + TILs low or high-density groups.

Statistical analysis

The correlations among clinical features were analyzed by Spearman’s test. For cross-tables, two-sided Fisher’s exact or Chi-square tests were used. Cox regression was used for univariate and multivariate analysis. Nomograms were generated using multivariate Cox regression coefficients. The discrimination of nomograms was evaluated by the C-index [23] and calibration curves. Calibration curves were used to express the relationship between the actual outcome frequencies and the predicted probabilities, with a bootstrapped sample of the study group. Kaplan-Meier curves were used to stratify tumor cases using various cut-off values calculated from the nomograms and to assess the performance of models. In this study, p-value < 0.05 was considered significant. The statistical analyses were performed using software R (version 4.1.0; The packages of R software were used for statistical analyses and data visualization as follows: “gmodels” for Fisher’s exact or Chi-square tests; “survival” and “survminer” for Cox regression; “rms” and “nomogramEx” for nomograms, calibration plots and calculating C-index and predicted score. “ggplot2” and “ggpubr” for Kaplan-Meier plots.


Clinicopathological characteristics, and correlation of IHC markers with clinicopathological parameters

A summary of the clinicopathological characteristics of VSCC cases and the correlation between the biomarkers and individual clinicopathological parameters were presented in Table 1. A total of 69 patients with VSCC were included in this study, and the median follow-up was 72 (range 12–156) months. The median age of VSCC patients was 67 (range 29–91) years. Among 69 patients, 53 (76.8%) cases were FIGO stage I, 45 (65.2%) cases were grade 1 tumor, 63 (91.3%) cases were lymph node metastasis (LNM) negative, and 51 (73.9%) cases were HPV-independent (negative). Among 69 tumors, 30 (43.5%) were classified as p53 mutant, 27 (39.1%) were classified as Ki-67 high, 57 (82.6%) were classified as PD-L1 positive, and 48 (69.6%) were classified as CD8 + TILs high. As cases with positive LNM were classified as advanced stage, it was not surprising that the FIGO stage of tumor and LNM positivity had a moderately positive correlation (r = 0.440, p < 0.001) (Table S1). The pairwise comparisons of other clinical variables were not statistically significant.

Table 1 Association of risk markers with main clinicopathological features

We further investigated the relationship between clinical characteristics and the expression of markers (summarized in Table 1). The percentage of CD8 + TILs high tumors in advanced group (FIGO stage II-III) is significantly higher than that in FIGO I group (93.8%, 15/16 vs. 62.3%, 33/53, p = 0.027). The percentage of p53 mutant tumors was significantly higher in HPV-independent group than in HPV-associated group (54.9%, 28/51 vs. 11.1%, 2/18, p = 0.001). On the other hand, the percentage of Ki67 high tumors was significantly higher in HPV-associated group than in HPV-independent group (83.3%, 15/18 vs. 23.5%, 12/51, p < 0.001).

We also analyzed the relationship between the expression of IHC markers and CD8 + TILs (Table 1). CD8 + TILs appeared to be positively associated with p53 mutant status and PD-L1 positivity (p = 0.029 and p = 0.036, respectively). No statistically significant correlation was noted between other markers.

Survival analyses of various clinicopathological factors, biomarkers, and CD8 + TILs

As seen in Table 2, only advanced age (≥ 67 years) was significantly correlated with poorer OS in univariate COX models (p = 0.025). Multivariate analyses showed that the high Ki-67 index (HR: 7.899; p = 0.006) and advanced age (≥ 67 years) (HR: 5.899; p = 0.009) were significantly associated with poorer OS. In contrast, high CD8 + TILs (HR: 0.214; p = 0.024) and HPV-positivity (HR: 0.092; p = 0.016) were significantly associated with favorable OS. Meanwhile, poor PFS was significantly associated with PD-L1-positivity (HR: 5.311; p = 0.045), and high Ki-67 index (HR: 3.680; p = 0.042). High CD8 + TILs (HR: 0.236; p = 0.014) and HPV-positivity (HR: 0.116; p = 0.011) were also significantly associated with favorable PFS.

Table 2 Univariate analysis of OS and PFS

Construction of prognostic nomograms

Based on the prognostic factors from Cox models, a nomogram was constructed to predict OS and PFS (Fig. 1). To avoid the influence of the relatively small sample size, the variables with a more restricted p < 0.02 were selected to predict OS, including age (< 67 or ≥ 67 years), HPV (negative or positive), Ki-67 index (low or high), PD-L1 expression by CPS (< 1 or ≥ 1) and CD8 + TILs density (low or high). The prognostic factors selected for predicting PFS included age (< 67 or ≥ 67 years), LNM (negative or positive), HPV (negative or positive), Ki-67 index (low or high), PD-L1 expression by CPS (< 1 or ≥ 1) and CD8 TILs density (low or high). In the nomograms, a higher total score based on the sum of all factors was associated with a worse outcome. For instance, a 60-year-old patient VSCC that is HPV-negative, high Ki-67 index, PD-L1-negative, and low CD8 + TILs would have a total of 248 points (0 points for age, 100 points for HPV-negative, 88 points for high Ki-67 index, 0 points for PD-L1-negative and 60 points for low CD8 + TILs) for a predicted 2-year and 3-year OS of 91.6% and 88.7%, respectively. Similarly, a 70-year-old patient with VSCC that is HPV-negative, lymph node-positive, high Ki-67 index, PD-L1-positive, and high CD8 + TILs would have a total of 334 points (51 points for age, 100 points for HPV-negative, 53 points for lymph node-positive, 65 points for high Ki-67 index, 65 points for PD-L1 positive, and 0 points for high CD8 + TILs). For this patient, the predicted 2-year PFS was 26.7%, and the predicted 3-year PFS was 15.3%.

Fig. 1
figure 1

Prognostic nomograms for VSCC. (A) The nomogram to predict 2-year OS and 3-year OS was created based on 5 independent prognostic factors. (B) The nomogram to predict 2-year PFS and 3-year PFS was created based on 6 independent prognostic factors

Validation of prognostic nomograms

VSCC patients in these nomograms had a C-index of 0.754 (95% CI [confidence interval], 0.631–0.876) and 0.754 (95% CI, 0.668–0.841) for OS and PFS, respectively. A bootstrap resampling was used to select 1,000 samples for the validation cohorts. Further testing of these nomograms’ discriminative and calibrating abilities was carried out using calibration curves for OS and PFS (Fig. 2A-D). It showed that the predicted 3-year OS and PFS models were more consistent with actual survival probability when compared with calibration plots for 5-year OS and PFS, respectively. The corrected C-index for OS and PFS of calibration curves in validation cohorts (n = 1000) were 0.699 and 0.683, respectively.

Fig. 2
figure 2

The calibration curve of the nomogram for predicting 2-year OS (A), 3-year OS (B), 2-year PFS (C), and 3-year PFS (D) in the validation cohort. The nomogram-predicted probability of OS (PFS) is plotted on the x-axis and the actual probability is on the y-axis. Kaplan-Meier curves demonstrating OS (E) and PFS (F) in VSCC patients according to mean scores of nomogram’s total points (< mean scores vs. ≥ mean scores)

To further evaluate the performance of the nomograms, we calculated the total score for every VSCC patient by the OS and PFS model. Among patients, the median total score for OS and PFS nomogram were 230 and 216, respectively. By using median total scores as the cut-off value, patients were divided into two groups (low score or high score). Kaplan-Meier curves were presented for the survival outcome of this cohort (Fig. 2E, F). Compared with patients with low scores, patients with scores (> 230 for the OS model or > 216 for the PFS model) had a substantially worse OS (p = 0.049) or PFS (p = 0.0012).


Despite the downward trend of uVIN / HSIL in young women after the introduction of HPV vaccine, the downward trend did not happen in the incidence of VSCC and even significantly increased in the general population [24], which was partially driven by global aging [25]. Radical local excision is still the standard of care for VSCC, even for tumors at an early stage, which may cause high morbidity and poor quality of life. Besides traditional clinicopathological risk factors such as FIGO stage, LNM, age, etc., biomarkers also demonstrated prognostic significance in vulvar cancers [7, 17, 19, 21, 26,27,28,29,30]. In this study, a comprehensive approach that took consideration of all known risk factors was used in an attempt to search for better risk stratification of patients with VSCC to direct potentially less aggressive treatments in low-risk patients.

Similar to results previously reported [31], our data showed that advanced age, HPV-independent status, and positive LNM were associated with adverse survival. However, FIGO stage of the tumor showed no prognostic significance in our study. This may be due to the small size of patients with advanced stages (FIGO III and IV) in our cohort. Several studies have investigated the prognostic significance of FIGO stages of VSCC with inconsistent results. Lei L et al. established a prediction model using 2,166 VSCC patients in the SEER (Surveillance, Epidemiology, and End Results) database and also found that the FIGO staging system lost its effectiveness in evaluating prognosis[32]. In their predictive model, patients with stage III tumors had a lower prognosis score than patients with stage II tumors (higher scores indicate worse prognoses), contrary to common sense. Another study analyzed the survival predictors of 6,792 patients from the same database and also found that neither FIGO nor AJCC (American Joint Committee on Cancer) staging system had predictability of prognoses in VSCC [33]. In contrast, Jin L et al. found that stage was a strong prognostic factor for VSCC using 18,985 cases from the SEER database. It is worth noting that the staging system (SEER staging system) was used in the Jin L et al. study not based on FIGO or AJCC staging system and only divided tumors into three substages (stage I - localized, stage II - regional, or stage III - distant) [34]. Mao Y et al. observed that advanced AJCC and TNM (tumor, nodes, metastasis) stage but not SEER stage was correlated with adverse survival outcomes in their screened SEER cohorts (4681 VSCC patients) [35]. Another important prognostic clinical factor was LNM, the status of which was closely related to tumor staging, risk of recurrence, and decision on postoperative adjuvant therapy. In this study, we found that LNM was a negative predictor for PFS but not for OS in multivariate models. Many previous studies supported that LNM was strongly correlated with both OS and PFS [31, 33, 35]. Of note, a multicenter retrospective study showed that adjuvant therapy (radiotherapy or chemoradiotherapy) significantly improved the 3-year PFS in VSSC patients with LNM compared with those who did not receive postoperative adjuvant therapy [36]. However, the 3-year OS was not improved significantly [36].

In this study, we also included biomarkers: p16 and p53 associated with HPV status and classification [4, 7, 18, 21, 31, 37], Ki-67 related to tumor proliferation and differentiation [27,28,29, 38], and PD-L1 and CD8 + TILs linked with tumor immune microenvironment [16, 17, 19,20,21, 30]. The HPV status represented by p16 IHC was considered to be associated with the prognosis of VSSC, with HPV-independent tumors having worsened prognosis [31, 37, 39, 40]. The mutant p53 was commonly observed in HPV-independent dVIN or LS-associated vulvar cancers [4]. Kortekaas KE et al. further stratified p16-negative VSSC patients by using p53 IHC, and found that patients with p16-/p53mut tumor had the worst outcomes, with advanced stages, deeper invasion, and more frequent lymphovascular space invasion [7]. Ki-67 has not received as much attention as p53 in the research on vulvar cancers in recent years. It seems to the lackluster of Ki-67 was caused by its lack of correlation with tumor classification, survival, or LNM [27, 28, 41]. Stewart CJ et al. reported increased Ki-67 expression in the periphery of tumor nests and reduced at the invasive front in p16-positive VSCC. In contrast, Ki-67 expression is more diffuse in p16-negative tumors, particularly in higher-grade lesions [38]. Our findings supported p53 status as a risk stratification factor and suggested a potential role of Ki-67 in the subclassification of VSCC (Table 1). Interestingly, Ki-67 had more prognostic predictive value than p53 in both multivariate and nomogram models of our study (Table 3; Fig. 1). In addition, Kaplan-Meier curves showed no significant difference in survival between p53-negative and p53-positive in HPV- negative patients of our cohort (Figure S1). A possible cause was that VSCC patients included in this study were concentrated in stage IB and lack of more malignant events (advanced stages, LNM, etc.), which might skew the predictive sensitivity of Ki-67.

Table 3 Multivariate analyses of OS and PFS

As the most studied immune checkpoint (IC) pathway, the PD-1/PD-L1 axis function through the interaction between PD-1 present in T-cells and PD-L1 expressed in various cell types including tumor and immune cells. Success of the anti-PD-1 and anti-PD-L1 inhibitors have shown promising efficacy in many tumor types [42], including vulvar cancer [43]. We herein reported that frequent PD-L1 expression was detected in VSCC tumors and tumor-infiltrating immune cells (TPS ≥ 1% in 59.4% and CPS ≥ 1 in 82.6% of the current cohort). Our final prognostic nomograms showed that PD-L1 positivity by CPS was a strong predictor for OS and PFS. So far, PD-L1 expression in vulvar cancer has been investigated in a few studies, with conflicting results. Compared with various cutoff values of PD-L1 expression (1%, 50% for TPS and 10, 50 for CPS), Czogalla B et al. demonstrated that only PD-L1 positivity by CPS was correlated with the VSCC patients’ outcome in their study [20]. A study by Cocks M et al. in which standard TPS or CPS was not used, instead a cutoff of 1% positive cells was used, showed that PD-L1 expression was found in 43% of tumor cells, with higher proportions in intratumoral (67%) and peritumoral (81%) immune cells [30], and higher PD-L1 expression and high CD8 + TILs were associated with disease recurrence, overall mortality, and cancer mortality [30]. In contrast, the study by Sznurkowski JJ et al. suggested that immune cells with PD-L1-positivity were a favorable prognostic factor for VSCC patients [19]. Our data suggest that low CD8 + TILs as an independent prognostic factor were associated with poor OS and PFS. Unlike previously reported [19, 30, 44], no significant correlation between CD8 + TILs and PD-L1 expression was observed in this study. It is worth noting that his results from those studies were also difficult to compare as different cutoffs for the definition of PD-L1 positivity were used. Moreover, the prognostic value of CD8 + TILs was also difficult to compare because of variation in the proportion of enrolled patients with advanced diseases, which may significantly skew the result because higher CD8 + TILs were likely linked with advanced-stage cases [44].

This study has some limitations: (1) Relatively small sample size (n = 69). Future multi-center studies that include larger cohorts are needed for further validation of this study; (2) In this study, enrolled cases are mostly stage I, and stage IV case was completely missing. The composition bias of patients may skew the final statistical analysis; (3) The follow-up was limited to 1–3 years in some cases, indicating that OS and PFS were probably not reached in some cases; (4) Other clinical features such as tumor size, depth of invasion, or postoperative adjuvant therapy were not included. Future studies that address those features are needed.


Inconsistent with previous studies, we found that shorter OS and PFS were associated with PD-L1-positive, higher Ki-67 expression, and low CD8 + TILs. LNM was only linked with poor PFS in VSCC patients. In addition, our study explored the main risk factors of VSCC from clinicopathological parameters and immunohistochemical panels by prognostic nomograms. Although our conclusions need to be confirmed by future studies with larger samples sizes, this data adds to the continued efforts of better risk stratification of VSCC patients, in hope of potentially less aggressive treatments in low-risk patients to decrease morbidity and improve quality of life.

Data Availability

Data supporting the findings of this study are available upon request from the corresponding author.



squamous cell carcinoma


vulvar squamous cell carcinoma


cervical squamous cell carcinoma


overall survival


progression-free survival


hazard ratio


confidence interval


tumor-infiltrating lymphocytes


combined positive score


usual vulvar intraepithelial neoplasia


high-grade squamous intraepithelial lesion


differentiated vulvar intraepithelial neoplasia


high-risk human papillomavirus


lichen sclerosus


International Federation of Gynecology and Obstetrics


lymph node metastasis




Surveillance, Epidemiology, and End Results


American Joint Committee on Cancer


immune checkpoint


  1. Virarkar M, Vulasala SS, Daoud T, Javadi S, Lall C, Bhosale P. Vulvar Cancer: 2021 revised FIGO Staging System and the role of imaging. Cancers (Basel) 2022, 14(9).

  2. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and Mortality Worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49.

    Article  PubMed  Google Scholar 

  3. Jenkins TM, Mills AM. Putative precancerous lesions of vulvar squamous cell carcinoma. Semin Diagn Pathol. 2021;38(1):27–36.

    Article  PubMed  Google Scholar 

  4. Cohen PA, Anderson L, Eva L, Scurry J. Clinical and molecular classification of vulvar squamous pre-cancers. Int J Gynecol Cancer. 2019;29(4):821–8.

    Article  PubMed  Google Scholar 

  5. MacDuffie E, Sakamuri S, Luckett R, Wang Q, Bvochara-Nsingo M, Monare B, Bazzett-Matabele L, Moloi T, Ralefala T, Ramogola-Masire D, et al. Vulvar cancer in Botswana in women with and without HIV infection: patterns of treatment and survival outcomes. Int J Gynecol Cancer. 2021;31(10):1328–34.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Bigby SM, Eva LJ, Fong KL, Jones RW. The natural history of Vulvar Intraepithelial Neoplasia, differentiated type: evidence for Progression and Diagnostic Challenges. Int J Gynecol Pathol. 2016;35(6):574–84.

    Article  CAS  PubMed  Google Scholar 

  7. Kortekaas KE, Bastiaannet E, van Doorn HC, de Vos PJ, Ewing-Graham PC, Creutzberg CL, Akdeniz K, Nooij LS, van der Burg SH, Bosse T, et al. Vulvar cancer subclassification by HPV and p53 status results in three clinically distinct subtypes. Gynecol Oncol. 2020;159(3):649–56.

    Article  CAS  PubMed  Google Scholar 

  8. Merlo S. Modern treatment of vulvar cancer. Radiol Oncol. 2020;54(4):371–6.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Olawaiye AB, Cotler J, Cuello MA, Bhatla N, Okamoto A, Wilailak S, Purandare CN, Lindeque G, Berek JS, Kehoe S. FIGO staging for carcinoma of the vulva: 2021 revision. Int J Gynaecol Obstet. 2021;155(1):43–7.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Davis AA, Patel VG. The role of PD-L1 expression as a predictive biomarker: an analysis of all US Food and Drug Administration (FDA) approvals of immune checkpoint inhibitors. J Immunother Cancer. 2019;7(1):278.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Arora S, Balasubramaniam S, Zhang W, Zhang L, Sridhara R, Spillman D, Mathai JP, Scott B, Golding SJ, Coory M, et al. FDA approval Summary: Pembrolizumab plus Lenvatinib for Endometrial Carcinoma, a Collaborative International Review under Project Orbis. Clin Cancer Res. 2020;26(19):5062–7.

    Article  CAS  PubMed  Google Scholar 

  12. Makker V, Colombo N, Casado Herráez A, Santin AD, Colomba E, Miller DS, Fujiwara K, Pignata S, Baron-Hay S, Ray-Coquard I et al. Lenvatinib plus Pembrolizumab for Advanced Endometrial Cancer. N Engl J Med 2022.

  13. Ferrall L, Lin KY, Roden RBS, Hung CF, Wu TC. Cervical Cancer immunotherapy: facts and hopes. Clin Cancer Res. 2021;27(18):4953–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Clancy AA, Spaans JN, Weberpals JI. The forgotten woman’s cancer: vulvar squamous cell carcinoma (VSCC) and a targeted approach to therapy. Ann Oncol. 2016;27(9):1696–705.

    Article  CAS  PubMed  Google Scholar 

  15. Howitt BE, Sun HH, Roemer MG, Kelley A, Chapuy B, Aviki E, Pak C, Connelly C, Gjini E, Shi Y, et al. Genetic basis for PD-L1 expression in squamous cell carcinomas of the Cervix and Vulva. JAMA Oncol. 2016;2(4):518–22.

    Article  PubMed  Google Scholar 

  16. Choschzick M, Gut A, Fink D. PD-L1 receptor expression in vulvar carcinomas is HPV-independent. Virchows Arch. 2018;473(4):513–6.

    Article  CAS  PubMed  Google Scholar 

  17. Lerias S, Esteves S, Silva F, Cunha M, Cochicho D, Martins L, Felix A. CD274 (PD-L1), CDKN2A (p16), TP53, and EGFR immunohistochemical profile in primary, recurrent and metastatic vulvar cancer. Mod Pathol. 2020;33(5):893–904.

    Article  CAS  PubMed  Google Scholar 

  18. Sznurkowski JJ, Zawrocki A, Biernat W. Local immune response depends on p16INK4a status of primary tumor in vulvar squamous cell carcinoma. Oncotarget. 2017;8(28):46204–10.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Sznurkowski JJ, Zawrocki A, Sznurkowska K, Peksa R, Biernat W. PD-L1 expression on immune cells is a favorable prognostic factor for vulvar squamous cell carcinoma patients. Oncotarget. 2017;8(52):89903–12.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Czogalla B, Pham D, Trillsch F, Rottmann M, Gallwas J, Burges A, Mahner S, Kirchner T, Jeschke U, Mayr D, et al. PD-L1 expression and survival in p16-negative and -positive squamous cell carcinomas of the vulva. J Cancer Res Clin Oncol. 2020;146(3):569–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Garganese G, Inzani F, Fragomeni SM, Mantovani G, Della Corte L, Piermattei A, Santoro A, Angelico G, Giaco L, Corrado G et al. The Vulvar Immunohistochemical Panel (VIP) Project: Molecular Profiles of Vulvar Squamous Cell Carcinoma. Cancers (Basel) 2021, 13(24).

  22. Humphries MP, Maxwell P, Salto-Tellez M. QuPath: the global impact of an open source digital pathology system. Comput Struct Biotechnol J. 2021;19:852–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Harrell FE Jr, Califf RM, Pryor DB, Lee KL, Rosati RA. Evaluating the yield of medical tests. JAMA. 1982;247(18):2543–6.

    Article  PubMed  Google Scholar 

  24. Rasmussen CL, Thomsen LT, Aalborg GL, Kjaer SK. Incidence of vulvar high-grade precancerous lesions and cancer in Denmark before and after introduction of HPV vaccination. Gynecol Oncol. 2020;157(3):664–70.

    Article  PubMed  Google Scholar 

  25. Khadraoui H, Thappa S, Smith M, Davidov A, Castellanos MR. Age-associated trends of vulvar cancer in the US. Menopause. 2020;28(2):119–25.

    Article  PubMed  Google Scholar 

  26. Zhang T, Liu Q, Yu M, Lan Y, Zhou J. Expression profiles reveal involvement of VEGF, IGF1, BIRC5, and MMP1 in Vulvar Carcinogenesis. Technol Cancer Res Treat. 2021;20:15330338211004922.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Hantschmann P, Lampe B, Beysiegel S, Kurzl R. Tumor proliferation in squamous cell carcinoma of the vulva. Int J Gynecol Pathol. 2000;19(4):361–8.

    Article  CAS  PubMed  Google Scholar 

  28. Modesitt SC, Groben PA, Walton LA, Fowler WC Jr, Van Le L. Expression of Ki-67 in vulvar carcinoma and vulvar intraepithelial neoplasia III: correlation with clinical prognostic factors. Gynecol Oncol. 2000;76(1):51–5.

    Article  CAS  PubMed  Google Scholar 

  29. Takacs FZ, Radosa JC, Bochen F, Juhasz-Boss I, Solomayer EF, Bohle RM, Breitbach GP, Schick B, Linxweiler M. Section 62/Ki67 and p16/Ki67 dual-staining immunocytochemistry in vulvar cytology for the identification of vulvar intraepithelial neoplasia and vulvar cancer: a pilot study. Arch Gynecol Obstet. 2019;299(3):825–33.

    Article  CAS  PubMed  Google Scholar 

  30. Cocks M, Chaux A, Jenson EG, Miller JA, Rodriguez Pena MDC, Tregnago AC, Taheri D, Eich ML, Sharma R, Vang R, et al. Immune checkpoint status and tumor microenvironment in vulvar squamous cell carcinoma. Virchows Arch. 2020;477(1):93–102.

    Article  CAS  PubMed  Google Scholar 

  31. Julia CJ, Hoang LN. A review of prognostic factors in squamous cell carcinoma of the vulva: evidence from the last decade. Semin Diagn Pathol. 2021;38(1):37–49.

    Article  PubMed  Google Scholar 

  32. Lei L, Tan L, Zhao X, Zeng F, Xu D. A prognostic nomogram based on lymph node ratio for postoperative vulvar squamous cell carcinoma from the Surveillance, Epidemiology, and end results database: a retrospective cohort study. Ann Transl Med. 2020;8(21):1382.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Zhou W, Yue Y. Developing and validating Novel Nomograms for Predicting the overall survival and Cancer-specific survival of patients with primary vulvar squamous cell Cancer. Front Med (Lausanne). 2021;8:777605.

    Article  PubMed  Google Scholar 

  34. Liu J, Wang M. Development and validation of nomograms predicting cancer-specific survival of vulvar cancer patients: based on the Surveillance, Epidemiology, and end results program. Int J Gynaecol Obstet. 2022;156(3):529–38.

    Article  PubMed  Google Scholar 

  35. Mao Y, He M, Tang Z, Chen M, Wu L, Liang T, Huang J. Prognostic nomograms to predict overall survival and cause specific death in vulvar squamous cell carcinoma. Int J Gynecol Cancer. 2022;32(6):706–15.

    Article  PubMed  Google Scholar 

  36. Mahner S, Jueckstock J, Hilpert F, Neuser P, Harter P, de Gregorio N, Hasenburg A, Sehouli J, Habermann A, Hillemanns P et al. Adjuvant therapy in lymph node-positive vulvar cancer: the AGO-CaRE-1 study. J Natl Cancer Inst 2015, 107(3).

  37. Rasmussen CL, Sand FL, Hoffmann Frederiksen M, Kaae Andersen K, Kjaer SK. Does HPV status influence survival after vulvar cancer? Int J Cancer. 2018;142(6):1158–65.

    Article  CAS  PubMed  Google Scholar 

  38. Stewart CJ, Crook ML. Fascin and cyclin D1 immunoreactivity in non-neoplastic vulvar squamous epithelium, vulvar intraepithelial neoplasia and invasive squamous carcinoma: correlation with Ki67 and p16 protein expression. J Clin Pathol. 2014;67(4):319–25.

    Article  CAS  PubMed  Google Scholar 

  39. Hinten F, Molijn A, Eckhardt L, Massuger L, Quint W, Bult P, Bulten J, Melchers WJG, de Hullu JA. Vulvar cancer: two pathways with different localization and prognosis. Gynecol Oncol. 2018;149(2):310–7.

    Article  CAS  PubMed  Google Scholar 

  40. Wakeham K, Kavanagh K, Cuschieri K, Millan D, Pollock KG, Bell S, Burton K, Reed NS, Graham SV. HPV status and favourable outcome in vulvar squamous cancer. Int J Cancer. 2017;140(5):1134–46.

    Article  CAS  PubMed  Google Scholar 

  41. Emanuels AG, Burger MP, Hollema H, Koudstaal J. Quantitation of proliferation-associated markers Ag-NOR and Ki-67 does not contribute to the prediction of lymph node metastases in squamous cell carcinoma of the vulva. Hum Pathol. 1996;27(8):807–11.

    Article  CAS  PubMed  Google Scholar 

  42. Tang Q, Chen Y, Li X, Long S, Shi Y, Yu Y, Wu W, Han L, Wang S. The role of PD-1/PD-L1 and application of immune-checkpoint inhibitors in human cancers. Front Immunol. 2022;13:964442.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Shapira-Frommer R, Mileshkin L, Manzyuk L, Penel N, Burge M, Piha-Paul SA, Girda E, Lopez Martin JA, van Dongen MGJ, Italiano A, et al. Efficacy and safety of pembrolizumab for patients with previously treated advanced vulvar squamous cell carcinoma: results from the phase 2 KEYNOTE-158 study. Gynecol Oncol. 2022;166(2):211–8.

    Article  CAS  PubMed  Google Scholar 

  44. Kortekaas KE, Santegoets SJ, Tas L, Ehsan I, Charoentong P, van Doorn HC, van Poelgeest MIE, Mustafa DAM, van der Burg SH. Primary vulvar squamous cell carcinomas with high T cell infiltration and active immune signaling are potential candidates for neoadjuvant PD-1/PD-L1 immunotherapy. J Immunother Cancer 2021, 9(10).

Download references


Not applicable.


Not applicable.

Author information

Authors and Affiliations



The data in the study were fully accessible to Feng Zhou. Feng Zhou and Hao Chen are responsible for data integrity and accuracy. Study concept and design: Feng Zhou and Tao Zhang. Acquisition of data: Yingfan Zhu. Statistical analysis and interpretation of data: Tao Zhang, Yingfan Zhu, Hao Chen. Drafting of the manuscript: Tao Zhang. Revising or critically reviewing the manuscript: Feng Zhou, Hao Chen, Shuang Niu, Jie Luo, Juanqing Li.

Corresponding authors

Correspondence to Hao Chen or Feng Zhou.

Ethics declarations

Competing interests

The authors state they have no competing interests.

Statement of Ethics

All procedures performed in studies involving human participants were following the ethical standards of the national and/or national research committee and with the Helsinki declaration. Informed consent was obtained from each patient before their samples and records were used for scientific research. The study was approved by the Institutional Review Board at Zhejiang University School of Medicine Women’s Hospital, China (No.IRB-20200158-R).

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, T., Zhu, Y., Luo, J. et al. An integrated model for prognosis in vulvar squamous cell carcinoma. BMC Cancer 23, 534 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: