Researchers reviewed patients treated at four Chinese centers from October 2019 through December 2025. One center supplied a training cohort of 546 patients, while three independent centers supplied an external validation cohort of 344. Disease-free survival events occurred in 172 training participants and 93 external-validation participants. Predictors were selected using least absolute shrinkage and selection operator-penalized Cox regression and bootstrap stability selection. The resulting nomogram incorporated ypN stage, perineural invasion, major pathological response, ypT stage, sex, body mass index category and lymphovascular invasion.

The model’s discrimination was 0.741 (95% confidence interval, 0.702–0.780) in the training cohort and 0.701 (0.644–0.757) in external validation. Optimism-corrected C-indices were 0.726 (0.688–0.762) for fixed-model validation and 0.706 (0.668–0.747) when predictor selection was repeated. In the external cohort, the C-index difference between the nomogram and categorical ypTNM staging was 0.048 (0.014–0.082). External calibration showed reasonable agreement between predicted and observed disease-free survival at one and two years, but the model overpredicted disease-free survival at three years. Decision-curve analysis indicated greater net benefit than ypTNM staging within specified threshold ranges.

Using a fixed cutoff derived from the training cohort, patients classified as high risk had poorer disease-free survival in both the training cohort (hazard ratio, 3.86; 95% confidence interval, 2.75–5.44) and the external validation cohort (hazard ratio, 3.40; 95% confidence interval, 2.16–5.35; both P<0.001). The results support further evaluation of the nomogram for individualized postoperative risk estimates among patients with ESCC treated with neoadjuvant chemoimmunotherapy followed by surgery. Because the evidence presented here comes from a retrospective study and an early-access abstract, the reported performance does not establish clinical benefit, and prospective validation remains necessary.

Subject of Research: External validation of a postoperative disease-free survival prediction model in esophageal squamous cell carcinoma

Article Title: Development and external validation of a nomogram to predict disease-free survival after neoadjuvant chemoimmunotherapy and surgery in esophageal squamous cell carcinoma: a multicenter retrospective study

Article References: Ao, Y., Leng, C., Shao, L., Liu, G., Li, K., Chen, J., Huang, Y., Luo, K., Liu, Q., Zhao, L., Peng, S., & Fu, J. (2026). Development and external validation of a nomogram to predict disease-free survival after neoadjuvant chemoimmunotherapy and surgery in esophageal squamous cell carcinoma: a multicenter retrospective study. BMC Cancer. https://doi.org/10.1186/s12885-026-17164-y

Image Credits: AI Generated

DOI: 10.1186/s12885-026-17164-y

Keywords: esophageal squamous cell carcinoma, neoadjuvant chemoimmunotherapy, esophagectomy, disease-free survival, prognostic nomogram, external validation, retrospective cohort, ypTNM staging, Development, external, validation, nomogram

The study, published in PLOS Pathogens by Yu Zhang, Peng Wang and colleagues at the People’s Hospital of Xinjiang Uygur Autonomous Region, focused on the viral gene K15, which sits at the right end of the KSHV genome and encodes a multi-pass transmembrane signaling protein. K15 exists in two highly divergent alleles, known as the prototype (P) and minority (M) forms. In their cytoplasmic signaling domains, the two variants share less than 33 percent amino acid homology, a degree of divergence that suggests they may engage different molecular partners inside infected cells and, potentially, shape disease in different ways.

Xinjiang, a historical crossroads on the Silk Road, offered an unusually informative setting. The region has a high prevalence of Kaposi sarcoma and co-circulating viral genotypes rarely seen together in Western cohorts. Of the 147 patients who passed quality control and genotyping, 107, or 72.8 percent, carried the K15M variant, while 40 carried K15P. That distribution echoes patterns reported in classic Kaposi sarcoma cohorts from Japan and Taiwan and hints that host genetic and evolutionary pressures in Central Asian populations may have favored the M form.

The clinical picture that emerged was striking and, at first glance, paradoxical. Patients carrying the M genotype were significantly less likely to be coinfected with HIV, at 10.3 percent versus 27.5 percent among P carriers, yet they showed higher levels of systemic inflammation, measured by the Systemic Immune-Inflammation Index (SII), the neutrophil-to-lymphocyte ratio, and neutrophil counts. They also suffered lower limb edema far more often, at 37.4 percent versus 20.0 percent, and were less likely to have mucosal involvement. After adjusting for tumor stage, demographics and CD4 T-cell counts, K15M carriage remained an independent predictor of edema, with 2.6-fold increased odds, and of a high inflammatory burden, with an adjusted odds ratio of 5.43 for elevated SII.

To probe whether inflammation actually lies on the causal path between viral genotype and edema, the team used causal mediation analysis, a statistical framework that decomposes an association into direct and indirect components. The Systemic Immune-Inflammation Index significantly mediated 29.0 percent of the genotype-associated effect on edema, with a P value of 0.009. A reverse mediation model, testing whether edema led to inflammation rather than the other way around, failed to reach significance, supporting inflammation’s position upstream in the pathway. Dose-response analysis sharpened the picture further: among K15M carriers, edema risk rose linearly with increasing SII, with an odds ratio of 1.58 per 500-unit increase, whereas no such gradient existed in K15P carriers. The inflammation-edema link, in other words, appears intrinsically tied to the viral genotype.

The mechanistic plausibility rests on the structure of the K15 protein. Its signaling capacity resides in a C-terminal cytoplasmic tail containing SH2- and SH3-binding motifs that recruit Src-family kinases and TRAF adaptor proteins to activate the pro-inflammatory NF-kB and MAPK pathways. The P form has been well characterized as mobilizing these cascades through specific tyrosine-based motifs. The M form, by contrast, shows reduced dependence on the canonical YEEV motif for NFAT activation, and the authors hypothesize that its structurally distinct tail may confer enhanced affinity for inflammatory adaptors or lack the negative regulatory phosphorylation sites present in the P type. Such differences could produce constitutive, unchecked signaling that sustains high-grade systemic inflammation, which in turn promotes vascular permeability and the tissue swelling that clinicians observe as edema.

The genotype also carried prognostic weight. Kaplan-Meier analysis showed significantly inferior progression-free survival among K15M carriers, with a log-rank P value of 0.017, and multivariate Cox modeling yielded an adjusted hazard ratio of 1.87, a borderline but robust estimate confirmed across multiple censoring scenarios in sensitivity analyses. Notably, the deleterious effect was most pronounced in patients with localized disease, where the hazard ratio reached 4.32, suggesting that viral biology can flag danger even when the tumor appears anatomically confined. A dedicated sensitivity analysis restricted to classic Kaposi sarcoma patients preserved the inflammatory signature of K15M, arguing against clinical subtype as a confounder.

To convert these biological insights into a usable clinical instrument, the researchers built a six-factor prognostic nomogram using LASSO Cox regression with cross-validation, maintaining an events-per-variable ratio of 11.2. The model anchors on the K15 genotype and visceral involvement, supplemented by CD4 count, procalcitonin, the lymphocyte-to-monocyte ratio and the neutrophil-to-lymphocyte ratio, the latter two selected over SII to avoid collinearity. The tool achieved a concordance index of 0.761, corrected to 0.743 after bootstrapping with 5,000 resamples, and time-dependent ROC analysis showed areas under the curve above 0.80 at one, two and three years.

The head-to-head comparison with conventional staging was decisive. The nomogram achieved an area under the curve of 0.830, significantly outperforming anatomical stage alone at 0.563 and visceral involvement alone at 0.530, with P values of 0.003 and below 0.001 respectively. Reclassification metrics confirmed substantial gains in predictive accuracy, and decision curve analysis demonstrated net clinical benefit across a wide range of threshold probabilities. When patients were stratified by nomogram score, the high-risk group showed a median progression-free survival of 11.0 months versus 40.0 months in the low-risk group, a separation with a P value below 0.0001 that held regardless of HIV status or tumor burden.

The authors are careful to frame their conclusions within the limits of a single-center, retrospective design. Edema was assessed qualitatively rather than with quantitative metrics, a small fraction of viral genotypes remained unclassified, possibly reflecting recombination or untyped variants, and the mediation results are presented as biologically plausible associations rather than definitive causal proof, since no wet-lab cytokine assays were performed on the archival samples. Even so, the implications are considerable. If the K15M genotype sustains an NF-kB-driven inflammatory program independent of immunodeficiency, then carriers may represent a subgroup amenable to anti-inflammatory or immunomodulatory strategies layered onto conventional therapy, with genotyping serving as a companion diagnostic. More broadly, the study argues that Kaposi sarcoma risk assessment should move from anatomical observation toward biology-driven precision oncology, incorporating the genetics of the virus itself into the clinical calculus, particularly in regions where the M genotype predominates.

Subject of Research: Association of KSHV K15 genetic variants with Kaposi sarcoma aggressiveness and inflammation

Article Title: KSHV K15 genetic heterogeneity is associated with Kaposi sarcoma aggressiveness through modulation of the host inflammatory microenvironment

Article References: Zhang, Y., Wang, P., Zhang, J., Wang, Y., Li, T., Ding, Y., & Kang, X. (2026). KSHV K15 genetic heterogeneity is associated with Kaposi sarcoma aggressiveness through modulation of the host inflammatory microenvironment. PLOS Pathogens, 22(10), e1014615. https://doi.org/10.1371/journal.ppat.1014615

Image Credits: AI Generated

DOI: 10.1371/journal.ppat.1014615

Keywords: KSHV, Kaposi sarcoma, K15 genotype, inflammation, herpesvirus, edema, prognostic nomogram, precision oncology, mediation analysis, NF-kB, HIV, viral genotyping

The research, published in BMC Cancer by a team from Dokuz Eylül University in Izmir, took the form of a single-center retrospective comparison. The investigators combed their institutional records for patients with localized, resectable soft tissue sarcoma of the extremities who underwent curative-intent surgery between 2008 and 2024. They settled on 41 patients, a modest number by any standard, and followed them for a median of 103 months, more than eight and a half years. During that time, 12 patients died, every one of them from sarcoma itself rather than from other causes. The five-year overall survival rate in the cohort was 78.0 percent, falling to 61.1 percent at ten years, figures that sit comfortably within the range reported for extremity sarcomas in larger international series.

To judge the two nomograms, the researchers relied on two complementary statistical concepts that are central to modern prognostic modeling. The first is discrimination, measured here with Harrell’s C-index, which asks how well a model separates patients who die earlier from those who live longer. A C-index of 0.5 means the model performs no better than a coin flip, while a value of 1.0 represents perfect ordering of every patient’s outcome. The second is calibration, which asks a subtler question: when the model says a patient has, say, a 70 percent chance of surviving five years, do roughly 70 percent of similar patients actually make it that far? A tool can rank patients correctly yet still be badly miscalibrated, promising more or less survival than reality delivers, and both dimensions matter when the numbers end up in a clinic note or a consent discussion.

Because the two tools were designed to answer questions at different time points, the comparison required careful methodological choices. The MSKCC nomogram generates predictions at four, eight, and twelve years after surgery, while Sarculator produces five- and ten-year estimates. The team used each horizon-specific prediction as a prognostic marker and computed C-index values over the full follow-up period, attaching bias-corrected and accelerated bootstrap 95 percent confidence intervals to every estimate. They prespecified a single paired comparison at the closest available horizons, Sarculator’s five-year prediction against the MSKCC four-year prediction, and were explicit that this contrast does not test identical prediction targets. With only 12 deaths in the entire cohort, they treated all discrimination and calibration findings as exploratory and hypothesis-generating, emphasizing uncertainty over p-values.

Against that cautious backdrop, the headline finding was clear enough. The MSKCC nomogram produced a higher C-index point estimate, hovering around 0.81 across its prediction horizons, compared with roughly 0.71 for Sarculator. In the prespecified paired comparison, the difference in C-index was 0.096, with a 95 percent confidence interval stretching from 0.004 to 0.225. The statistical tests told slightly different stories: a Wald test suggested the difference was significant at p equals 0.042, while a paired bootstrap test gave a p-value of 0.072, which fails the conventional significance threshold. The authors were refreshingly candid about this discordance, concluding that the wide interval, the mismatched horizons, and the small number of events together preclude any claim that one tool is definitively superior to the other.

Calibration told a similar story of cautious asymmetry. When the researchers plotted predicted survival against observed survival, the MSKCC nomogram’s estimates tracked the actual experience of the cohort most closely at the four- and eight-year marks. Sarculator, by contrast, tended to overestimate survival, and the discrepancy was most pronounced at the ten-year horizon, where the tool’s optimism diverged furthest from what the Izmir patients actually experienced. Overestimating survival is not a trivial flaw. A model that paints too rosy a picture could, in principle, lead clinicians to under-treat a high-risk patient or to schedule follow-up less intensively than the underlying biology warrants, although the authors stress that their small cohort prevents any precise quantification of how large this miscalibration really is.

Why should a comparison of 41 patients matter to anyone beyond the walls of a single Turkish sarcoma clinic? The answer lies in a persistent gap in the validation literature. Both nomograms were developed and refined in large, predominantly Western cohorts, and head-to-head comparisons restricted exclusively to extremity-localized disease, and conducted in non-Western populations, have been scarce. Soft tissue sarcomas are a heterogeneous family of more than 70 histological subtypes, and the composition of cases, the referral patterns, and even the prevalence of undifferentiated pleomorphic sarcoma versus other subtypes can vary between regions. A tool that performs beautifully in New York or Milan may drift when applied in Izmir, and the only way to find out is to test it, even imperfectly, in new settings.

The study’s technical approach also offers a small masterclass in how prognostic tools should be evaluated. Rather than simply reporting a single C-index and moving on, the investigators used horizon-specific predictions as the markers being tested, acknowledged that comparing a five-year forecast with a four-year forecast is an apples-to-oranges exercise, and leaned on bootstrap resampling to quantify uncertainty honestly. The bias-corrected and accelerated bootstrap method they employed adjusts for skewness and bias in the resampled distribution, producing confidence intervals that are more reliable in small samples than naive approximations. Their decision to prespecify a single primary comparison also guards against the inflation of false positives that comes from testing many contrasts and cherry-picking the significant ones, a discipline that small retrospective studies often lack.

The limitations, which the authors enumerate with unusual transparency, are nonetheless substantial. Forty-one patients and twelve events provide very little statistical fuel; a rough rule of thumb in prognostic modeling suggests that reliable estimation requires far more events per variable examined. The retrospective single-center design means the cohort reflects one institution’s referral patterns, surgical practices, and pathology reporting over a 16-year span, during which imaging, staging, and adjuvant therapy norms all evolved. Calibration could only be assessed graphically rather than with formal statistical tests, and the different prediction horizons of the two tools mean the head-to-head comparison is inherently approximate. The authors themselves conclude that no inference of comparative superiority can be drawn, and they frame the work explicitly as hypothesis-generating, calling for confirmation in larger, externally validated cohorts.

Even so, the study lands at a meaningful moment. Prediction tools in oncology are proliferating rapidly, powered by ever-larger registries and increasingly sophisticated machine learning methods, yet the quiet work of external validation, especially in populations far from the development data, often lags behind. Nomograms like MSKCC’s and calculators like Sarculator are already embedded in clinical practice, quoted in tumor boards and counseling sessions around the world. This Turkish analysis does not dethrone either tool, but it does something arguably more valuable: it demonstrates a rigorous, honest template for testing them, and it raises a concrete, testable hypothesis that the older MSKCC model may discriminate better while the newer Sarculator may run optimistic at long horizons. For the thousands of patients who face an extremity sarcoma diagnosis each year, the eventual answer to that hypothesis, tested in large and diverse cohorts, could mean survival estimates they can genuinely trust.

Subject of Research: Comparison of the MSKCC and Sarculator prognostic nomograms for predicting survival in extremity soft tissue sarcoma

Article Title: Discrimination and calibration of the MSKCC and sarculator nomograms in extremity soft tissue sarcoma: a single-center retrospective comparison

Article References: İzgör, R. B., Özalp, F. R., Aktepe, O. H., Karaoğlu, A., & Atağ, E. (2026). Discrimination and calibration of the MSKCC and sarculator nomograms in extremity soft tissue sarcoma: a single-center retrospective comparison. BMC Cancer. https://doi.org/10.1186/s12885-026-17087-8

Image Credits: AI Generated

DOI: 10.1186/s12885-026-17087-8

Keywords: soft tissue sarcoma, extremity sarcoma, MSKCC nomogram, Sarculator, prognostic nomogram, overall survival, C-index, calibration, external validation, retrospective study, BMC Cancer, Dokuz Eylül University