Baseline clinical and characteristics
A total of 71 patients with osteosarcoma (OSC) were included for retrospective study. 39 (54.9%) of these patients were male, and 32 (45.1%) were female; the median age was 25 (range 3–83) years. According to 8th edition of the AJCC TNM staging criteria, the number of stages I&II and III&IV was 51 (71.8%) and 20 (28.2%), respectively. The median follow-up for OS and PFS were 34 months and 32 months respectively. The 1-, 3-, and 5-year OS rates were 70.4%, 38.0%, and 14.1%; the 1-, 3-, and 5-year PFS rates were 69.0%, 31.0%, and 11.3%. Baseline characteristics of the total OSC patients were shown in Table 1.
Table 1
Demographics and clinical characteristics of OSC patients
Variable | No. (%) or Mean ± sd |
Characteristics | |
Age (years) | 28.0 ± 18.4 |
Gender | |
Male | 39 (54.9%) |
Female | 32 (45.1%) |
Smoke | |
Yes | 4 (5.6%) |
No | 67 (94.4%) |
Family history of cancer | |
Yes | 2 (2.8%) |
No | 69 (97.2%) |
Tumor site | |
Extremities | 40 (56.3%) |
Pelvis/Spine | 4 (5.6%) |
Skull | 19 (26.8) |
Other | 8 (11.3) |
Tumor size (cm)a | 6.6 ± 3.3 |
Tumor border | |
Well-defined | 21 (29.6%) |
Ill-defined | 34 (47.9%) |
Unrecorded | 16 (22.5%) |
Treatment | |
None | 2 (2.8%) |
Sur | 27 (38.0%) |
Rad/Che | 8 (11.3%) |
Sur and Rad/Che | 32 (45.1%) |
Other | 2 (2.8%) |
TNM stageb | |
I&II | 51 (71.8%) |
III&IV | 20 (28.2%) |
Laboratory data | |
WBC (109/L) | 7.6 ± 2.6 |
Neutrophil (109/L) | 4.7 ± 2.4 |
Lymphocyte (109/L) | 2.1 ± 0.6 |
Monocyte (109/L) | 0.5 ± 0.2 |
PLT (109/L) | 278.1 ± 86.4 |
NLR | 2.4 ± 1.5 |
LMR | 4.7 ± 3.3 |
PLR | 141.5 ± 59.1 |
dNLR | 1.7 ± 0.9 |
SII | 681.8 ± 453.9 |
PNI | 54.0 ± 7.6 |
RBC (1012/L) | 4.8 ± 0.6 |
HGB (g/L) | 130.8 ± 20.9 |
IP3+ (mmol/L) | 1.49 ± 1.4 |
Ca2+ (mmol/L) | 2.5 ± 1.0 |
Mg2+ (mmol/L) | 0.9 ± 0.1 |
Gap | 13.7 ± 4.9 |
ALT (U/L) | 19.6 ± 14.8 |
AST (U/L) | 21.9 ± 11.1 |
LSR | 0.9 ± 0.5 |
ALP (U/L) | 460.5 ± 1187.6 |
LDH (U/L) | 259.6 ± 260.9 |
GGT (U/L) | 22.3 ± 11.3 |
TP (g/L) | 72.7 ± 6.4 |
ALB (g/L) | 43.4 ± 7.0 |
GLOB (g/L) | 29.8 ± 4.4 |
CRP (mg/L) | 7.7 ± 14.0 |
AGR | 1.48 ± 0.3 |
ACR | 45.2 ± 59.2 |
TBIL (umol/L) | 10.3 ± 5.2 |
DBIL (umol/L) | 3.4 ± 1.6 |
IBIL (umol/L) | 6.8 ± 3.9 |
TBA (umol/L) | 4.8 ± 6.3 |
Urea (mmol/L) | 4.6 ± 1.7 |
CRE (umol/L) | 57.1 ± 19.0 |
Cys-C (mg/L) | 0.8 ± 0.2 |
UA (umol/L) | 352.3 ± 95.9 |
CHO (mmol/L) | 4.4 ± 1.1 |
TG (mmol/L) | 1.1 ± 0.6 |
HDL-C (mmol/L) | 1.2 ± 0.4 |
LDL-C (mmol/L) | 3.4 ± 6.3 |
LHR | 2.8 ± 4.3 |
APOA (g/L) | 1.2 ± 0.3 |
APOB (g/L) | 0.8 ± 0.3 |
ABR | 1.6 ± 0.6 |
AI | 2.7 ± 1.1 |
GLU (mmol/L) | 4.8 ± 0.8 |
a: The tumor maximum diameter; |
b: TNM stage was classified according to the AJCC 8th TNM staging system; |
Abbreviations: TNM: Tumor Node Metastasis stage; Sur: surgery; Rad: radiotherapy; Che: chemotherapy; PLT: platelet; NLR: neutrophil / lymphocyte ratio; LMR: lymphocyte / monocyte ratio; PLR: platelet / lymphocyte ratio; dNLR: derived neutrophil-to-lymphocyte ratio; SII: systemic immune-inflammation index; PNI: prognostic nutritional index; RBC: red blood cell; HGB: hemoglobin; IP3+: serum phosphorus; Ca2+: serum calcium; Mg2+: serum magnesium; Gap: anion gap; ALT: alanine aminotransferase; AST: aspartate aminotransferase; LSR: ALT / AST ratio; ALP: alkaline phosphatase; LDH: lactic dehydrogenase; GGT:glutamyl transpeptidase; TP: total protei; ALB: albumin; GLOB: globulin; CRP: C-reactive protein, AGR: ALB / GLOB ratio; ACR: ALB / CRP ratio; TBIL: total bilirubin; DBIL: direct bilirubin; IBIL: indirect bilirubin; TBA: total bile acid; CRE: creatinine; Cys-C: cystatin C; UA: uric acid; CHO: total cholesterol; TG: triglycerides; HDL-C: high density lipoprotein cholesterol; LDL-C: low density lipoprotein cholesterol; LHR: LDL-C / HDL-C ratio; APOA: apolipoprotein A1; APOB: apolipoprotein B; ABR: APOA / APOB ratio; AI: The atherogenic index; GLU: glucose. |
Construction Of Prognostic Model For Os And Pfs
Firstly, the LASSO regression analysis was performed to extract significant predictors associated with overall survival (OS). Figure 1A showed the change in trajectory of each predictor was analyzed. Afterwards, the optimal value for λ was determined using 10-fold cross-validation with the minimum criteria (Fig. 1B). According to the criteria, the optimal value of the λ was 0.076 in this study, and its corresponding predictors were considered to be the significant prognostic factors for OS, which included RBC, Ca2+, CRE, PNI, and LSR. Finally, a prognostic model was constructed for predicting OS and PFS based on the coefficients of significant predictors derived from the LASSO regression, with a risk score was calculated by using the following formula: The prognostic model risk score = 0.191 - (0.077 × RBC) + (0.048 × Ca2+ - (0.007 × CRE) - (0.006 × PNI) - (0.726 × LSR). In this formula, each variable value represents their respective serum levels
Assessing the performance between the novel prognostic model, TNM staging, and clinical treatment
In order to determine the incremental predictive value of the novel prognostic model to traditional TNM staging and clinical treatment for OS and PFS. Hence, we introduced C-index, tdROC curve, DCA, NRI, and IDI to evaluate the predictive accuracy of the novel prognostic model, TNM staging, and clinical treatment.
Firstly, we calculated the C-index in the three predictive signatures, as shown in Table 2. For OS, the C-index of the novel prognostic model was 0.782 (95% CI = 0.658–0.905), which was higher than that of the TNM staging [0.593 (95% CI = 0.458–0.728), P = 0.088] and clinical treatment [0.521 (95% CI = 0.400–0.643), P < 0.001]. For PFS, the C-index of the novel prognostic model was 0.741 (95% CI = 0.632–0.851), which was significantly higher than that of the TNM staging [0.544 (95% CI = 0.433–0.656), P = 0.013] and clinical treatment [0.505 (95% CI = 0.392–0.617), P < 0.001]. Secondly, we plotted tdROC curves and calculated the corresponding AUCs in the three predictive signatures. Results showed the dynamic AUC levels of the novel prognostic model estimated exceeding 0.75 both in OS and PFS, which were higher than TNM staging and clinical treatment (Fig. 2). Thirdly, the DCA showed the novel prognostic model had a higher overall net benefit than TNM staging and clinical treatment across the majority of the range of reasonable threshold probabilities both in OS and PFS (Fig. 3). Finally, both the NRI and IDI calculations were obtained at 1, 3 and 5 years and used to compare the alternative prognostic indices of our model with the TNM staging and clinical treatment. The results were presented in Table 3. For OS, NRI analysis revealed that the accuracy of the novel prognostic model was higher than that of the TNM staging [for 1-year survival (0.538, P = 0.030), 3-year survival (0.324, P = 0.289), and 5-year survival (0.211, P = 0.706)] and clinical treatment [for 1-year survival (0.385, P = 0.070), 3-year survival (0.367, P = 0.149), and 5-year survival (0.216, P = 0.478)]. IDI analysis showed that the discrimination ability the novel prognostic model was also higher than that of the TNM staging [for 1-year survival (0.193, P = 0.050), 3-year survival (0.165, P = 0.139), and 5-year survival (0.153, P = 0.468)] and clinical treatment [for 1-year survival (0.212, P = 0.010), 3-year survival (0.202, P = 0.070), and 5-year survival (0.207, P = 0.189)]. In addition, the similar results also showed that the novel prognostic model had a good performance in predicting the PFS for OSC patients than others.
Table 2
The C-index of OS and PFS for our model, TNM stage, and treatment.
Models for survival prediction | C-index | 95 CI% | P |
For OS | | | |
Our model | 0.782 | 0.658–0.905 | |
TNM stage | 0.593 | 0.458–0.728 | |
Treatment | 0.521 | 0.400–0.643 | |
Our model vs TNM stage | | | 0.088 |
Our model A vs Treatment | | | < 0.001 |
For PFS | | | |
Our model | 0.741 | 0.632–0.851 | |
TNM stage | 0.544 | 0.433–0.656 | |
Treatment | 0.505 | 0.392–0.617 | |
Our model vs TNM stage | | | 0.013 |
Our model A vs Treatment | | | < 0.001 |
C-index = concordance index; P values are calculated based on normal approximation using function rcorrp.cens in Hmisc package. |
Table 3
A comparison of discriminatory ability of Our model with TNM stage and Treatment using NRI and IDI for OS and PFS.
| 1-Year | 3-Year | 5-Year |
| NRI | P | IDI | P | NRI | P | IDI | P | NRI | P | IDI | P |
For OS | | | | | | | | | | | | |
Our model vs TNM stage | 0.538 | 0.030 | 0.193 | 0.050 | 0.324 | 0.289 | 0.165 | 0.139 | 0.211 | 0.706 | 0.153 | 0.468 |
Our model vs Treatment | 0.385 | 0.070 | 0.212 | 0.010 | 0.367 | 0.149 | 0.202 | 0.070 | 0.216 | 0.478 | 0.207 | 0.189 |
For PFS | | | | | | | | | | | | |
Our model vs TNM stage | 0.528 | 0.040 | 0.127 | 0.050 | 0.287 | 0.259 | 0.136 | 0.129 | 0.401 | 0.239 | 0.139 | 0.169 |
Our model vs Treatment | 0.374 | 0.050 | 0.135 | 0.010 | 0.333 | 0.129 | 0.154 | 0.050 | 0.276 | 0.219 | 0.143 | 0.139 |
Construction of a predictive nomogram based on prognostic model risk score, TNM staging, and clinical treatment
The nomogram incorporating the prognostic model risk score, TNM staging, and clinical treatment to predict the probability of 1-, 3-, and 5-year OS (Fig. 4A) and PFS (Fig. 4B) in OSC patients. Each patient would assign one point for each prognostic variable, the estimated probability of 1-, 3- and 5- year OS and PFS was determined by summing all of the point, and the higher number of total points indicated a worse outcome for the patient. In addition, the calibration curve showed good agreement between prediction and observation in 1-, 3-, and 5-year OS (Fig. 4C, 4E, 4H) and PFS (Fig. 4D, 4F, 4I). The C-index of the nomogram for OS and PFS was 0.784 and 0.737, respectively.
The correlation between the prognostic model, TNM staging and clinical treatment
Currently, AJCC TNM staging system remains the most valuable tool to predict prognosis for OSC. Next, we assessed the correlation between the prognostic model, TNM staging and clinical treatment (Fig. 5). In the plot, the blue represented positive correlation, and the red represented negative correlation. The color intensity and the size of the circle were proportional to the correlation coefficients. Significant linear dependence between variables was identified using Pearson's correlation coefficient (PCC). The results showed that the prognostic model was positive correlation with TNM staging (PCC = 0.17, P = 0.150) and clinical treatment (PCC = 0.10, P = 0.423).
Survival analyses of OSC patients according to prognostic model risk score
Using the R package “survminer” and “survival”, we classified patients into low -risk patients and high-risk patients based on the prognostic model risk score, and make the Kaplan-Meier curve. The results showed that patients with higher risk scores (risk score > -0.94) had a significantly lower OS (Fig. 6A, P < 0.001) and PFS (Fig. 6B, P = 0.001) rate than their low-risk counter-parts (risk score ≤ -0.94). In order to test whether the prognostic model could remedy the current deficiencies of AJCC TNM stage. Patients were factitiously stratified into early stage (stage I/II) and late stage (stage III/IV). Kaplan-Meier curve showed that high-risk patients in the early stage had significantly shorter OS (Fig. 6C, P < 0.001) and PFS (Fig. 6D, P < 0.001) than low-risk patients, but in the late stage, the OS (Fig. 6E, P = 0.220) and PFS (Fig. 6F, P = 0.450) in low-risk patients and high-risk patients displayed no significant difference.
The serum levels for the 5 selected predictors in the low-risk and high-risk patients
Figure 7 showed the pretreatment serum values of RBC, Ca2+, CRE, PNI, and LSR in the low-risk and high-risk patients. The serum values of RBC (4.87 ± 0.53 1012/L), CRE (60.75 ± 17.09 umol/L), PNI (54.66 ± 7.54), and LSR (0.99 ± 0.43) in the low-risk patients, were significantly higher than high-risk patients (RBC (4.07 ± 0.79 1012/L), CRE (32.26 ± 9.44 umol/L), PNI (49.31 ± 6.11), and LSR (0.35 ± 0.17). But the low-risk patients had a lower Ca2+ levels (2.34 ± 0.10 mmol/L) compared with high-risk patients (3.23 ± 2.65 mmol/L).