The letter responds directly to a recent study by Kirkham and colleagues, published in the same journal, that followed children with mild sleep-disordered breathing who were managed with watchful waiting rather than immediate surgery. That study identified prognostic factors associated with progression of the condition, and the Turkish authors contend that such findings are at risk of being misinterpreted. If a child carries a feature that predicts worsening over time, the intuitive leap is that removing the obstructing tonsillar and adenoid tissue early would prevent that worsening, and that high-risk children therefore stand to gain the most from adenotonsillectomy. Yılmaz and his colleagues argue that this leap is logically unsound, and they ground their objection in a well-established framework from clinical epidemiology: the distinction between prognostic and predictive markers.

The distinction was crystallized in a widely cited 2015 paper by Kristel Ballman in the Journal of Clinical Oncology, which the letter authors invoke. A prognostic marker tells you something about the likely course of a disease or condition regardless of which treatment the patient receives. A predictive marker, by contrast, tells you something about the differential effect of a specific treatment, identifying patients in whom the therapy works better or worse than it does in others. A tumor biomarker may signal aggressive disease in every patient who carries it, yet only randomized evidence can show whether that same biomarker identifies patients who respond to a particular drug. The two concepts answer different questions, and conflating them can lead to treatment decisions that are not supported by evidence.

Applied to pediatric sleep medicine, the logic becomes clear. If a child with mild sleep-disordered breathing has characteristics associated with a higher likelihood of progression, those characteristics are prognostic. They suggest the child’s symptoms may worsen whether or not surgery is performed. They do not demonstrate that surgery will produce a larger improvement in that child than in a low-risk child. Only a predictive analysis, ideally within a randomized trial that formally tests for an interaction between the risk factor and treatment assignment, can establish differential treatment benefit. Without such an interaction analysis, claiming that high-risk children derive greater benefit from adenotonsillectomy extrapolates beyond what the data can support.

This is not merely a statistical quibble, because the strongest available evidence on the question comes from a landmark randomized clinical trial. In 2023, Redline and colleagues published in JAMA the results of a randomized trial of adenotonsillectomy for snoring and mild sleep apnea in children, a study that grew out of the Pediatric Adenotonsillectomy Trial for Snoring, or PATS, protocol described by Wang and colleagues in BMJ Open in 2020. That trial randomized children with mild sleep-disordered breathing to surgery or to watchful waiting and evaluated outcomes including behavioral measures and symptom resolution. The letter authors point to this randomized evidence as the appropriate standard against which claims of differential benefit must be tested, rather than observational progression data from cohorts of children managed without surgery.

The stakes of the distinction are considerable. Adenotonsillectomy, while generally safe, is a real surgical intervention carried out under general anesthesia, with associated risks of bleeding, infection, pain and the considerable burden that surgery imposes on children and families. If clinicians begin triaging children toward surgery on the basis of prognostic risk alone, families may be counseled toward an operation on the mistaken understanding that their child is precisely the kind of patient who benefits most. Conversely, if genuine predictive markers of surgical benefit do exist, identifying them properly could spare low-benefit children an unnecessary operation while directing those who would truly gain toward timely treatment. Either way, the answer determines how thousands of pediatric consultations unfold each year.

The watchful waiting study that prompted the letter adds an important empirical dimension to the debate. By demonstrating that many children with mild sleep-disordered breathing who are managed without immediate surgery do not progress, and by characterizing which children are more likely to worsen, it provides clinicians with genuinely useful information about the natural history of the condition. Natural history data of this kind are exactly what prognostic research is designed to deliver. The letter authors do not dispute the value of that data; what they dispute is the inferential step of converting prognosis into treatment guidance. Knowing that a subset of children tends to worsen over time does not reveal whether early surgery would have altered that trajectory, because the children in the watchful waiting cohort were, by design, not operated on.

There is also a broader lesson here for how medical evidence travels. Findings from observational cohorts are frequently repurposed, in review articles, guidelines and clinical conversations, as justification for interventions they were never designed to evaluate. The prognostic-predictive framework offers a simple safeguard: before using a risk marker to justify treatment, ask whether the marker was shown to modify the effect of that treatment in a randomized comparison. In oncology, where the framework was formalized, this discipline has reshaped how biomarkers are validated and how targeted therapies are prescribed. Sleep medicine, the letter suggests, should adopt the same rigor, particularly for a condition as common and as variably managed as mild pediatric sleep-disordered breathing.

For now, the practical message for clinicians and families is one of calibrated caution. Mild sleep-disordered breathing in children sits on a spectrum that ranges from benign primary snoring to frank obstructive sleep apnea, and the decision to operate should rest on the best randomized evidence available, on the severity and impact of symptoms, and on shared decision making that weighs the known benefits and burdens of surgery. A child’s risk of progression is relevant information, but it is information about the disease, not about the treatment. As Yılmaz, Özer and Topal emphasize, until studies demonstrate that specific risk factors predict differential benefit from adenotonsillectomy, prognostic risk alone cannot establish that high-risk children have more to gain from the operation. The distinction may sound like semantics, but in the clinic it is the difference between evidence-based surgery and surgery based on an inferential shortcut.

Subject of Research: The distinction between prognostic and predictive risk markers in deciding adenotonsillectomy benefit for children with mild sleep-disordered breathing

Article Title: Prognostic risk does not establish greater adenotonsillectomy benefit in children with mild sleep-disordered breathing

Article References: Yılmaz, E., Özer, N. K., & Topal, E. (2026). Prognostic risk does not establish greater adenotonsillectomy benefit in children with mild sleep-disordered breathing. Journal of Clinical Sleep Medicine, 22(1), Article 176. https://doi.org/10.1007/s44470-026-00196-3

Image Credits: AI Generated

DOI: 10.1007/s44470-026-00196-3

Keywords: adenotonsillectomy, pediatric sleep apnea, sleep-disordered breathing, prognostic markers, predictive markers, watchful waiting, randomized controlled trial, clinical decision making, snoring, biomarkers, evidence-based medicine, Journal of Clinical Sleep Medicine

Metastatic castration-resistant prostate cancer, abbreviated mCRPC, is the lethal stage of prostate disease in which tumors continue to grow despite androgen-deprivation treatment. The arrival of [177Lu]Lu-PSMA-617, a radiopharmaceutical that delivers beta radiation directly to prostate cancer cells expressing the prostate-specific membrane antigen, changed the treatment landscape after the pivotal VISION phase III trial established it as a standard of care. Yet the survival benefit varies enormously from one patient to the next. Some men live for years after treatment begins, while others progress within months. Weighing the potential benefit against the burden of repeated nuclear medicine cycles demands an honest estimate of prognosis, and that is precisely what a validated scoring system can provide.

The Bellmunt Risk Score was originally developed for a completely different cancer: metastatic urothelial carcinoma. In its original setting, it stratified patients with advanced transitional cell carcinoma who had failed platinum-based chemotherapy using three binary variables that are universally available in any oncology clinic. Each patient receives one point for an Eastern Cooperative Oncology Group performance status greater than zero, meaning any degree of functional impairment; one point for anemia, defined as a hemoglobin concentration below 10 grams per deciliter; and one point for the presence of liver metastases. The resulting score ranges from zero to three, with higher scores indicating worse expected survival. Its elegance lies in its simplicity: no specialized software, no genomic sequencing, no additional laboratory panels.

In a recent primary analysis, the same research group showed that the score translates surprisingly well to prostate cancer patients undergoing PSMA-targeted radioligand therapy. But a demonstration in the development cohort is only the first step. Clinical prediction models are notorious for performing well in the population where they were built and then faltering elsewhere, a phenomenon statisticians call overfitting. External validation in a genuinely independent patient population, treated under different institutional pathways and evaluated by investigators uninvolved in the original data collection, is the mandatory test of generalizability. The new study was designed to meet exactly that standard.

The validation cohort comprised 243 men with confirmed PSMA-positive metastatic castration-resistant prostate cancer who received at least one cycle of [177Lu]Lu-PSMA-617 at University Hospital Frankfurt, a tertiary high-volume center with no patient overlap with the original development cohort. The score was calculated at baseline, within twenty-eight days before the first therapy cycle. The patient population was heavily pretreated: 9.9 percent received radioligand therapy as the first treatment line for metastatic disease, 22.6 percent as the second, 39.1 percent as the third, and 28.4 percent in even later lines. Over a median follow-up of 17.7 months, 111 deaths occurred, corresponding to 45.7 percent of the cohort, providing substantial statistical power for survival analysis.

The results revealed a strikingly clean stepwise pattern. Patients with a score of zero, meaning none of the three risk factors, had an estimated median overall survival of 24.0 months. Each additional point shaved months off that figure: 15.8 months for a score of one, 11.2 months for a score of two, and 8.7 months for the small group of seven patients with all three risk factors. The Kaplan-Meier comparison across the four groups was highly significant, with a log-rank p value below 0.0001. In univariable analysis, compared with the low-risk group, the hazard ratio for death was 1.63 for score one, 3.38 for score two, and 5.30 for score three, and these estimates aligned closely with the hazard ratios observed in the original development cohort.

Because more heavily pretreated patients naturally have worse survival, the researchers adjusted their multivariable analysis for the number of prior treatment lines. Even after this adjustment, the score remained an independent predictor of survival. The hazard ratio was 3.04 for score two and 4.76 for score three, both statistically significant, while score one showed a non-significant trend at 1.49. Given that only seven patients fell into the highest-risk category, the team performed a sensitivity analysis using Firth’s penalized likelihood Cox regression, a method designed for small sample sizes, which confirmed the stability of the estimate with a hazard ratio of 5.10.

Predictive accuracy was assessed with two complementary metrics. Harrell’s concordance index for the multivariable model combining the score and treatment line reached 0.659, comparable to the performance achieved in the development cohort. Time-dependent receiver operating characteristic analysis, which evaluates discrimination at specific time points, yielded area-under-the-curve values of 69.3 percent for six-month survival, 71.3 percent for twelve-month survival, and 67.5 percent for twenty-four-month survival. Calibration for twelve-month survival, examined with two hundred bootstrap resamples, was excellent, with a mean absolute error of just 0.027 and a maximum absolute error of 0.059, meaning the predicted and observed survival probabilities were nearly identical.

The authors are candid about the study’s limitations. The retrospective design and the absence of a central review of imaging data introduce potential bias, since liver metastases were identified through local institutional interpretation of PSMA PET/CT scans. The multivariable model deliberately adjusted only for treatment lines, omitting established prognostic markers such as baseline PSA, lactate dehydrogenase, alkaline phosphatase, and quantitative metastatic burden, which leaves open the possibility of residual confounding. The researchers argue that this restraint was intentional: adding complex variables would risk overfitting and would compromise the score’s identity as a strictly clinical, standalone, bedside-ready tool. The very small size of the score-three subgroup also demands cautious interpretation of its survival estimates.

What emerges is a pragmatic message for oncology. More sophisticated nomograms that incorporate quantitative PSMA-PET volume metrics or extended biochemical panels may theoretically offer superior accuracy, but they require specialized software or additional laboratory costs and are often impractical in routine care. The Bellmunt Risk Score, by contrast, can be computed in seconds from information already gathered at every oncology visit. As indications for [177Lu]Lu-PSMA-617 expand into earlier treatment lines following trials such as ENZA-p, which tested the radioligand in combination with enzalutamide, the need for rapid risk stratification will only grow. The researchers emphasize that the score is intended to complement, not replace, comprehensive clinical and imaging assessment, serving primarily to guide patient expectations and support shared decision-making. With external validation now complete, a tool born in urothelial carcinoma has earned a place in the prostate cancer clinic, offering clinicians and patients alike a clear-eyed, evidence-based starting point for one of the most consequential conversations in modern cancer care.

Subject of Research: External validation of the Bellmunt Risk Score for predicting overall survival in metastatic castration-resistant prostate cancer patients undergoing lutetium-177 PSMA-617 radioligand therapy

Article Title: External validation of the bellmunt risk score for survival prediction in mCRPC patients undergoing [177Lu]Lu-PSMA-617 therapy

Article References: Büttner, T., Wenzel, M., Mandel, P., Schmitt, P., Hoffmann, C., Marinova, M., Essler, M., Chun, F. K. H., Ritter, M., Groener, D., & Krausewitz, P. (2026). External validation of the bellmunt risk score for survival prediction in mCRPC patients undergoing [177Lu]Lu-PSMA-617 therapy. European Journal of Nuclear Medicine and Molecular Imaging. https://doi.org/10.1007/s00259-026-08169-7

Image Credits: AI Generated

DOI: 10.1007/s00259-026-08169-7

Keywords: metastatic castration-resistant prostate cancer, Bellmunt Risk Score, Lu-PSMA-617, radioligand therapy, survival prediction, prognostic markers, external validation, PSMA PET, overall survival, Kaplan-Meier analysis, Cox regression, nuclear medicine

Extensive-stage small cell lung cancer accounts for the majority of small cell lung cancer diagnoses at presentation, meaning the disease has already spread beyond the chest. The modern treatment paradigm pairs platinum-based chemotherapy with immune checkpoint inhibitors, and in selected patients who respond well, sequential thoracic radiotherapy is added to consolidate control of disease in the chest. Yet even after this intensive sequence, outcomes vary enormously between individuals, and clinicians have historically lacked validated markers to re-evaluate prognosis once radiotherapy is complete. The new research addresses precisely this gap, asking whether blood-based signals measured at the post-radiotherapy checkpoint carry meaningful information about subsequent survival.

The prognostic nutritional index, or PNI, is a composite measure calculated from serum albumin concentration and peripheral lymphocyte count. It captures two biologically important dimensions: nutritional status and cellular immune competence. Low albumin reflects catabolic stress and poor nutritional reserve, while lymphopenia signals depleted adaptive immunity, a particular concern in patients receiving immunotherapy whose antitumor activity depends on functional T cells. Lactate dehydrogenase, by contrast, is an enzyme released when cells are damaged or turning over rapidly, and elevated serum levels have long been associated with high tumor burden and aggressive disease biology in small cell lung cancer.

The study retrospectively analyzed 203 patients with extensive-stage small cell lung cancer who had completed first-line chemoimmunotherapy followed by sequential thoracic radiotherapy and who reached the post-radiotherapy assessment point without death or disease progression. Blood samples were collected at two timepoints: before the start of systemic therapy and four to six weeks after completion of thoracic radiotherapy. The researchers dichotomized PNI at a cutoff of 56.7, determined through their analysis, and classified lactate dehydrogenase against the institutional upper limit of normal of 245 units per liter. Overall survival and progression-free survival were both calculated from the date of the post-radiotherapy assessment, ensuring that the prognostic signals reflected the post-treatment state rather than pretreatment characteristics.

The results were unambiguous. During follow-up, 147 deaths and 179 progression events occurred. Higher post-radiotherapy PNI was independently associated with better overall survival and progression-free survival, while elevated post-radiotherapy lactate dehydrogenase was associated with poorer outcomes on both endpoints. In multivariable models adjusting for other clinical factors, both markers retained their significance, suggesting that they capture prognostic information beyond what standard clinical variables provide. The findings align with a growing body of evidence that host factors, nutrition and immune status, modulate outcomes in the immunotherapy era, not merely tumor burden alone.

Perhaps the most intriguing result came from tracking how PNI changed over the course of treatment. The researchers grouped patients according to their transition from baseline to post-radiotherapy PNI categories and found that these trajectories provided additional prognostic information beyond the post-radiotherapy value alone, with statistical significance for both overall survival and progression-free survival. In practical terms, a patient whose nutritional-immune index held steady or improved through chemoimmunotherapy and radiotherapy fared differently from one whose index declined to the same final value, hinting that the direction of change carries its own biological message about treatment tolerance and reserve capacity.

By combining the two markers, the team constructed an exploratory post-radiotherapy risk stratification with three tiers. The separation was stepwise and clinically substantial: median overall survival was 27 months in the low-risk group, 14 months in the intermediate-risk group, and just 9 months in the high-risk group. Compared with the low-risk group, the high-risk group had markedly poorer overall survival, with a hazard ratio of 5.122 and a 95 percent confidence interval of 3.103 to 8.454, and poorer progression-free survival, with a hazard ratio of 2.918 and a 95 percent confidence interval of 1.835 to 4.642, both statistically significant. A more than threefold difference in median survival between the extremes, derived from two inexpensive blood tests, illustrates how much prognostic granularity routine laboratory data can provide when deployed at the right moment in the treatment course.

The authors subjected their main multivariable model to bootstrap internal validation, a statistical resampling technique that estimates how much a model’s apparent accuracy is inflated by overfitting to the development dataset. The optimism-corrected concordance indices were 0.685 for overall survival and 0.641 for progression-free survival, values that indicate moderate discriminative ability, respectable for a model built on routinely collected clinical variables but short of the performance needed for definitive clinical decision-making. The team was careful to frame the stratification as exploratory, emphasizing that prospective external validation in independent cohorts is required before the approach can be applied in clinical practice.

The implications, if validated, could be significant for how follow-up care is tailored after aggressive multimodality therapy. Patients identified as high risk at the post-radiotherapy checkpoint might be candidates for intensified surveillance imaging, earlier enrollment in clinical trials of escalation strategies, or closer attention to nutritional and supportive care, while low-risk patients might safely avoid unnecessary interventions. Because both markers are already measured in standard clinical practice, implementing such a stratification would require no new assays, no additional cost, and no change to treatment workflows, only a shift in when clinicians look at the numbers and what they infer from them.

The study also carries caveats inherent to its design. As a retrospective analysis from a single institution, it cannot exclude selection biases in which patients received sequential thoracic radiotherapy or reached the post-radiotherapy assessment, and the cutoff values for PNI and lactate dehydrogenase were derived from the same cohort in which they were tested, raising the familiar risk of optimistic thresholds. Still, the work adds to a compelling narrative in modern oncology: that the body’s own nutritional and inflammatory state, read through simple blood counts and chemistry panels, can be as informative as expensive molecular profiling. For a disease as relentless as extensive-stage small cell lung cancer, any tool that helps clinicians and patients see the road ahead more clearly is welcome news, and this study offers a promising, if still provisional, addition to the prognostic toolkit.

Subject of Research: Prognostic value of post-radiotherapy nutritional and metabolic blood markers in extensive-stage small cell lung cancer

Article Title: Post-radiotherapy prognostic nutritional index and lactate dehydrogenase for risk stratification in extensive-stage small cell lung cancer after completion of chemoimmunotherapy and sequential thoracic radiotherapy

Article References: Post-radiotherapy prognostic nutritional index and lactate dehydrogenase for risk stratification in extensive-stage small cell lung cancer after completion of chemoimmunotherapy and sequential thoracic radiotherapy. (n.d.). https://doi.org/10.1186/s12885-026-17062-3

Image Credits: AI Generated

DOI: 10.1186/s12885-026-17062-3

Keywords: extensive-stage small cell lung cancer, thoracic radiotherapy, chemoimmunotherapy, prognostic nutritional index, lactate dehydrogenase, risk stratification, overall survival, progression-free survival, prognostic markers, radiation oncology, biomarkers, oncology

Multiple myeloma is a cancer of plasma cells, the antibody-producing white blood cells that reside in the bone marrow. Despite remarkable therapeutic advances over the past two decades, including proteasome inhibitors, immunomodulatory drugs and, more recently, antibody-based and cellular therapies, the disease remains incurable, and outcomes vary dramatically between individual patients. Accurate risk stratification at diagnosis is therefore a central goal in myeloma care. The Revised International Staging System, or R-ISS, which combines serum markers such as beta-2 microglobulin and albumin with chromosomal abnormalities detected by interphase fluorescence in situ hybridization and lactate dehydrogenase levels, is the current standard for grouping patients into risk categories. Yet even this framework leaves substantial heterogeneity unexplained, and the authors of the new study argue that systemic inflammation and nutritional impairment, both of which are increasingly recognized as modulators of cancer progression and treatment tolerance, may complement established staging in clinically meaningful ways.

The systemic immune-inflammation index is calculated from a standard complete blood count as the product of the peripheral platelet and neutrophil counts divided by the lymphocyte count. Elevated values reflect a state of heightened systemic inflammation, characterized by increased neutrophil activity and relative lymphopenia, patterns that have been linked to tumor-promoting immune microenvironments in a range of malignancies. The prognostic nutritional index, by contrast, incorporates the absolute lymphocyte count together with serum albumin concentration, integrating immunological competence with visceral protein status. Malnutrition and immune depletion are common in multiple myeloma, driven by the disease itself through factors such as renal impairment, chronic inflammation and cytokine-mediated catabolism, and both are known to compromise the ability of patients to tolerate intensive chemotherapy regimens. The rationale for combining the two indices rests on the idea that inflammation and nutritional decline represent distinct but interacting biological axes, and that patients in whom both are deranged simultaneously should face the greatest risk.

To test this hypothesis, the investigators assembled a retrospective cohort of 164 patients with newly diagnosed multiple myeloma treated at their institution between 2017 and 2024. All patients had pretreatment blood counts and albumin measurements available before the initiation of first-line therapy. Rather than adopting arbitrary cutoffs for the two indices, the team derived thresholds from receiver operating characteristic curves targeting progression-free survival at 36 months, employing both cumulative and dynamic approaches and applying inverse probability of censoring weighting, a statistical technique that corrects for the bias introduced when patients are lost to follow-up. This yielded a cutoff of 382.34 for the SII and 35.40 for the PNI. From these thresholds the researchers constructed a simple 0-to-2-point SII-PNI score, in which points were assigned for elevated inflammation and for impaired nutritional status respectively.

The results were striking. Both progression-free survival and overall survival differed significantly across the score groups, with P values below 0.001 in each case. Patients with higher combined scores, indicating concurrent systemic inflammation and nutritional impairment, experienced markedly shorter times to disease progression and death. The association with progression-free survival was strongest in the early period after diagnosis and attenuated over time, a pattern the authors characterized through time-varying effect analyses, suggesting that the biological state captured by the score is most consequential during the initial phase of disease control when frontline therapy is working to establish remission.

Perhaps the most compelling findings emerged when the researchers dissected the four phenotypes defined by the two indices. Taking patients with low SII and high PNI, the most favorable combination, as the reference group, they calculated adjusted hazard ratios for progression-free survival of 1.997 for patients with high SII alone, 2.052 for those with low PNI alone, and 11.416 for patients with concurrent high SII and low PNI. The corresponding hazard ratios for overall survival were 2.986, 2.998 and 10.292. In other words, while either derangement alone roughly doubled the risk of progression or death, the simultaneous presence of both increased the risk of progression more than elevenfold and the risk of death more than tenfold. This multiplicative pattern supports the central premise of the study: inflammation and nutritional decline are not redundant markers of the same underlying process, but complementary signals whose concordance identifies a uniquely vulnerable patient population.

Importantly, the team did not stop at demonstrating associations. They subjected their score to a battery of validation procedures designed to guard against the optimism that plagues many prognostic models. Bootstrap internal validation confirmed the stability of the model’s performance, and calibration analyses assessed how closely predicted survival probabilities matched observed outcomes. Crucially, the investigators evaluated the incremental value of the SII-PNI score beyond age and the R-ISS, the two most important established predictors available at diagnosis. In a temporal validation cohort consisting of patients treated between 2022 and 2024, a cohort entirely separate from the patients used to derive the model, the Harrell concordance index for progression-free survival was a modest 0.519 when based on age plus R-ISS alone, barely better than a coin flip. When the development-derived SII-PNI score was added, the C-index rose to 0.777, a dramatic improvement in discriminatory capacity that persisted when the analyses were adjusted for treatment modality and other clinical factors.

The implications of these findings extend beyond the statistics. Because the SII and PNI are computed from a complete blood count and a serum albumin measurement, tests performed routinely in virtually every cancer patient worldwide, the combined score costs essentially nothing to obtain and requires no specialized equipment, genetic testing or central laboratory review. In health systems where R-ISS components such as interphase FISH are unavailable or delayed, the SII-PNI score could provide an immediately actionable first-pass risk assessment. Even in well-resourced centers, the score may identify high-risk patients within conventional staging categories, informing decisions about treatment intensification, early consideration of autologous stem cell transplantation, closer surveillance and proactive nutritional support. The authors caution, however, that the score is intended to provide complementary prognostic information rather than to replace established staging frameworks.

As with any single-center retrospective study, limitations warrant consideration. The cohort of 164 patients, while adequate for the analyses performed, is modest in size, and the cutoffs derived from this population will require confirmation in larger, multicenter and ideally prospective cohorts before the score can be recommended for widespread clinical use. Temporal validation within the same institution, though methodologically valuable, does not fully substitute for external validation across populations with different demographics, disease biology and treatment standards. The retrospective design also means that the score’s utility for guiding therapeutic decisions, rather than merely predicting outcomes, remains to be demonstrated in interventional studies. Nevertheless, the magnitude of the observed effects, the rigorous statistical methodology, including inverse probability of censoring weighting and bootstrap validation, and the striking improvement in predictive performance over conventional staging together make a persuasive case that the humble complete blood count, interpreted through the lens of inflammation and nutrition, still has much to teach oncologists about the trajectory of multiple myeloma.

The work was supported by the Fuyang Key Research and Development Program and the Scientific Research Project of the Fuyang Municipal Health Commission, with no funder involvement in study design, data analysis or the decision to publish. The study protocol was approved by the Ethics Committee of Fuyang People’s Hospital, which waived the requirement for informed consent owing to the retrospective nature of the research, and the study was conducted in accordance with the Declaration of Helsinki. The authors declare no competing interests, and the article is published open access under a Creative Commons license. If future studies confirm these results, a two-point score calculated from blood tests ordered on day one of care could become a routine companion to the R-ISS, helping ensure that the patients who need the most aggressive and attentive treatment are identified from the outset of their myeloma journey.

Subject of Research: A retrospective cohort study evaluating a combined systemic immune-inflammation index and prognostic nutritional index score for survival risk stratification in newly diagnosed multiple myeloma.

Article Title: Prognostic value of a combined systemic immune-inflammation index and prognostic nutritional index score for risk stratification in newly diagnosed multiple myeloma: a retrospective cohort study

Article References: Prognostic value of a combined systemic immune-inflammation index and prognostic nutritional index score for risk stratification in newly diagnosed multiple myeloma: a retrospective cohort study. (n.d.). https://doi.org/10.1007/s00277-026-07267-8

Image Credits: AI Generated

DOI: 10.1007/s00277-026-07267-8

Keywords: multiple myeloma, systemic immune-inflammation index, prognostic nutritional index, risk stratification, progression-free survival, overall survival, R-ISS, prognostic markers, retrospective cohort study, hematology, biomarkers, survival prediction