Nomograms in oncology: more than meets the eye Balachandran, Vinod P, Dr; Gonen, Mithat, PhD; Smith, J Joshua, MD ...
Lancet oncology/Lancet. Oncology,
04/2015, Volume:
16, Issue:
4
Journal Article
Peer reviewed
Open access
Summary Nomograms are widely used as prognostic devices in oncology and medicine. With the ability to generate an individual probability of a clinical event by integrating diverse prognostic and ...determinant variables, nomograms meet our desire for biologically and clinically integrated models and fulfill our drive towards personalised medicine. Rapid computation through user-friendly digital interfaces, together with increased accuracy, and more easily understood prognoses compared with conventional staging, allow for seamless incorporation of nomogram-derived prognosis to aid clinical decision making. This has led to the appearance of many nomograms on the internet and in medical journals, and an increase in nomogram use by patients and physicians alike. However, the statistical foundations of nomogram construction, their precise interpretation, and evidence supporting their use are generally misunderstood. This issue is leading to an under-appreciation of the inherent uncertainties regarding nomogram use. We provide a systematic, practical approach to evaluating and comprehending nomogram-derived prognoses, with particular emphasis on clarifying common misconceptions and highlighting limitations.
Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second deadliest cancer in the United States by 2025, with 5-year survival at less than 10%. In other recalcitrant cancers, ...immunotherapy has shown unprecedented response rates, including durable remissions after drug discontinuation. However, responses to immunotherapy in PDAC are rare. Accumulating evidence in mice and humans suggests that this remarkable resistance is linked to the complex, dueling role of the immune system in simultaneously promoting and restraining PDAC. In this review, we highlight the rationale that supports pursuing immunotherapy in PDAC, outline the key barriers that limit immunotherapy efficacy, and summarize the primary preclinical and clinical efforts to sensitize PDAC to immunotherapy.
Group 2 innate lymphoid cells (ILC2s) regulate inflammation and immunity in mammalian tissues
. Although ILC2s are found in cancers of these tissues
, their roles in cancer immunity and immunotherapy ...are unclear. Here we show that ILC2s infiltrate pancreatic ductal adenocarcinomas (PDACs) to activate tissue-specific tumour immunity. Interleukin-33 (IL33) activates tumour ILC2s (TILC2s) and CD8
T cells in orthotopic pancreatic tumours but not heterotopic skin tumours in mice to restrict pancreas-specific tumour growth. Resting and activated TILC2s express the inhibitory checkpoint receptor PD-1. Antibody-mediated PD-1 blockade relieves ILC2 cell-intrinsic PD-1 inhibition to expand TILC2s, augment anti-tumour immunity, and enhance tumour control, identifying activated TILC2s as targets of anti-PD-1 immunotherapy. Finally, both PD-1
TILC2s and PD-1
T cells are present in most human PDACs. Our results identify ILC2s as anti-cancer immune cells for PDAC immunotherapy. More broadly, ILC2s emerge as tissue-specific enhancers of cancer immunity that amplify the efficacy of anti-PD-1 immunotherapy. As ILC2s and T cells co-exist in human cancers and share stimulatory and inhibitory pathways, immunotherapeutic strategies to collectively target anti-cancer ILC2s and T cells may be broadly applicable.
Treatment with immune checkpoint inhibitors (ICI) has demonstrated clinical benefit for a wide range of cancer types. Because only a subset of patients experience clinical benefit, there is a strong ...need for biomarkers that are easily accessible across diverse practice settings. Here, in a retrospective cohort study of 1714 patients with 16 different cancer types treated with ICI, we show that higher neutrophil-to-lymphocyte ratio (NLR) is significantly associated with poorer overall and progression-free survival, and lower rates of response and clinical benefit, after ICI therapy across multiple cancer types. Combining NLR with tumor mutational burden (TMB), the probability of benefit from ICI is significantly higher (OR = 3.22; 95% CI, 2.26-4.58; P < 0.001) in the NLR low/TMB high group compared to the NLR high/TMB low group. NLR is a suitable candidate for a cost-effective and widely accessible biomarker, and can be combined with TMB for additional predictive capacity.
Hepatic resection of colorectal liver metastases is associated with long-term survival. This study analyzes actual 10-year survivors after resection of colorectal liver metastases, reports the ...observed rate of cure, and identifies factors that preclude cure.
A single-institution, prospectively maintained database was queried for all initial resections for colorectal liver metastases for the years 1992–2004. Observed cure was defined as actual 10-year survival with either no recurrence or resected recurrence with at least 3 years of disease-free follow-up. Clinical risk score was dichotomized into low (0–2) and high (3–5). Semiparametric proportional hazards mixture cure model was utilized to estimate probability of cure.
We included 1,211 patients with a median follow-up for survivors of 11 years. Median disease-specific survival was 4.9 years (95% CI: 4.4–5.3). 295 patients (24.4%) were actual 10-year survivors. The observed cure rate was 20.6% (n = 250). Among 250 cured patients, 192 (76.8%) had no recurrence and 58 (23.2%) had a resected recurrence with at least 3 years of disease-free follow-up. Extrahepatic disease (n = 88), carcinoembryonic antigen >200 ng/mL (n = 119), positive margin (n = 109), and >10 tumors (n = 31) had observed cure rates less than 10%. In cure model analysis, patients with both extrahepatic disease and high clinical risk score (n = 31) had an estimated probability of cure of 3.5%.
Actual 10-year survival after resection of colorectal liver metastases is 24% with an observed 20% cure rate. Patients with both high clinical risk score and extrahepatic disease have an estimated probability of cure less than 5%. When such factors are identified, strong consideration may be given to preoperative strategies, such as neoadjuvant chemotherapy, to help select patients for surgical therapy.
Background and Aim
Genetic alterations in intrahepatic cholangiocarcinoma (iCCA) are increasingly well characterized, but their impact on outcome and prognosis remains unknown.
Approach and Results
...This bi‐institutional study of patients with confirmed iCCA (n = 412) used targeted next‐generation sequencing of primary tumors to define associations among genetic alterations, clinicopathological variables, and outcome. The most common oncogenic alterations were isocitrate dehydrogenase 1 (IDH1; 20%), AT‐rich interactive domain–containing protein 1A (20%), tumor protein P53 (TP53; 17%), cyclin‐dependent kinase inhibitor 2A (CDKN2A; 15%), breast cancer 1–associated protein 1 (15%), FGFR2 (15%), polybromo 1 (12%), and KRAS (10%). IDH1/2 mutations (mut) were mutually exclusive with FGFR2 fusions, but neither was associated with outcome. For all patients, TP53 (P < 0.0001), KRAS (P = 0.0001), and CDKN2A (P < 0.0001) alterations predicted worse overall survival (OS). These high‐risk alterations were enriched in advanced disease but adversely impacted survival across all stages, even when controlling for known correlates of outcome (multifocal disease, lymph node involvement, bile duct type, periductal infiltration). In resected patients (n = 209), TP53mut (HR, 1.82; 95% CI, 1.08‐3.06; P = 0.03) and CDKN2A deletions (del; HR, 3.40; 95% CI, 1.95‐5.94; P < 0.001) independently predicted shorter OS, as did high‐risk clinical variables (multifocal liver disease P < 0.001; regional lymph node metastases P < 0.001), whereas KRASmut (HR, 1.69; 95% CI, 0.97‐2.93; P = 0.06) trended toward statistical significance. The presence of both or neither high‐risk clinical or genetic factors represented outcome extremes (median OS, 18.3 vs. 74.2 months; P < 0.001), with high‐risk genetic alterations alone (median OS, 38.6 months; 95% CI, 28.8‐73.5) or high‐risk clinical variables alone (median OS, 37.0 months; 95% CI, 27.6‐not available) associated with intermediate outcome. TP53mut, KRASmut, and CDKN2Adel similarly predicted worse outcome in patients with unresectable iCCA. CDKN2Adel tumors with high‐risk clinical features were notable for limited survival and no benefit of resection over chemotherapy.
Conclusions
TP53, KRAS, and CDKN2A alterations were independent prognostic factors in iCCA when controlling for clinical and pathologic variables, disease stage, and treatment. Because genetic profiling can be integrated into pretreatment therapeutic decision‐making, combining clinical variables with targeted tumor sequencing may identify patient subgroups with poor outcome irrespective of treatment strategy.
Checkpoint blockade immunotherapies enable the host immune system to recognize and destroy tumour cells. Their clinical activity has been correlated with activated T-cell recognition of neoantigens, ...which are tumour-specific, mutated peptides presented on the surface of cancer cells. Here we present a fitness model for tumours based on immune interactions of neoantigens that predicts response to immunotherapy. Two main factors determine neoantigen fitness: the likelihood of neoantigen presentation by the major histocompatibility complex (MHC) and subsequent recognition by T cells. We estimate these components using the relative MHC binding affinity of each neoantigen to its wild type and a nonlinear dependence on sequence similarity of neoantigens to known antigens. To describe the evolution of a heterogeneous tumour, we evaluate its fitness as a weighted effect of dominant neoantigens in the subclones of the tumour. Our model predicts survival in anti-CTLA-4-treated patients with melanoma and anti-PD-1-treated patients with lung cancer. Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies. By using an immune fitness model to study immunotherapy, we reveal broad similarities between the evolution of tumours and rapidly evolving pathogens.
Vaccines are the most impactful medicines to improve health. Though potent against pathogens, vaccines for cancer remain an unfulfilled promise. However, recent advances in RNA technology coupled ...with scientific and clinical breakthroughs have spurred rapid discovery and potent delivery of tumor antigens at speed and scale, transforming cancer vaccines into a tantalizing prospect. Yet, despite being at a pivotal juncture, with several randomized clinical trials maturing in upcoming years, several critical questions remain: which antigens, tumors, platforms, and hosts can trigger potent immunity with clinical impact? Here, we address these questions with a principled framework of cancer vaccination from antigen detection to delivery. With this framework, we outline features of emergent RNA technology that enable rapid, robust, real-time vaccination with somatic mutation-derived neoantigens—an emerging “ideal” antigen class—and highlight latent features that have sparked the belief that RNA could realize the enduring vision for vaccines against cancer.
Though pathogen vaccines are immensely successful, cancer vaccines are largely clinically ineffective. Guasp et al. outline features of emergent RNA cancer vaccines that have achieved recent immunologic breakthroughs with robust immunity against somatic mutation-derived neoantigens—an “ideal” antigen class—and appear poised to deliver clinical breakthroughs in upcoming years.
Cancer immunoediting
is a hallmark of cancer
that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice
, ...whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features-'non-selfness' based on neoantigen similarity to known antigens
, and 'selfness' based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer.
Background
Pancreatic cancer is a highly lethal cancer with no established a priori markers of survival. Existing nomograms rely mainly on post-resection data and are of limited utility in directing ...surgical management. This study investigated the use of quantitative computed tomography (CT) features to preoperatively assess survival for pancreatic ductal adenocarcinoma (PDAC) patients.
Methods
A prospectively maintained database identified consecutive chemotherapy-naive patients with CT angiography and resected PDAC between 2009 and 2012. Variation in CT enhancement patterns was extracted from the tumor region using texture analysis, a quantitative image analysis tool previously described in the literature. Two continuous survival models were constructed, with 70% of the data (training set) using Cox regression, first based only on preoperative serum cancer antigen (CA) 19-9 levels and image features (model A), and then on CA19-9, image features, and the Brennan score (composite pathology score; model B). The remaining 30% of the data (test set) were reserved for independent validation.
Results
A total of 161 patients were included in the analysis. Training and test sets contained 113 and 48 patients, respectively. Quantitative image features combined with CA19-9 achieved a c-index of 0.69 integrated Brier score (IBS) 0.224 on the test data, while combining CA19-9, imaging, and the Brennan score achieved a c-index of 0.74 (IBS 0.200) on the test data.
Conclusion
We present two continuous survival prediction models for resected PDAC patients. Quantitative analysis of CT texture features is associated with overall survival. Further work includes applying the model to an external dataset to increase the sample size for training and to determine its applicability.
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