Effects of high-protein supplementation during cancer therapy: a systematic review and meta-analysis.

This was a systematic review and meta-analysis that pooled data from 18 randomised controlled trials (RCTs) testing the effects of high-protein supplementation (HPS) in adults receiving cancer therapy.

**Intervention:** High-protein supplementation, defined as providing ≥20 g of additional protein per day beyond the patient's usual dietary intake. Supplements came in various forms: oral nutritional supplements (ready-to-drink shakes, powders), protein-enriched foods (e.g., high-protein yoghurt, pudding), or additional servings of protein-rich foods. The protein sources included whey, casein, soy, and mixed blends. Most interventions provided 20–40 g of extra protein daily, typically divided into 1–2 servings.

**Comparator:** Standard care (no supplement), placebo (low-protein or isocaloric low-protein supplement), or dietary advice alone. Some studies used a "usual diet" control; others used an isocaloric low-protein drink to control for energy intake.

**Primary outcomes:** Change in body weight (kg), change in lean body mass (LBM, kg), and change in handgrip strength (kg, a proxy for overall muscle strength).

**Secondary outcomes:** Change in physical function (e.g., 6-minute walk test, timed up-and-go), quality of life (measured by validated questionnaires such as EORTC QLQ-C30), nutritional status (e.g., PG-SGA score), and adverse events (gastrointestinal tolerance, renal function).

The meta-analysis included 18 RCTs with a total of 1,847 participants.

**Population:** Adults (≥18 years) diagnosed with any type of cancer (solid tumours or haematological malignancies) who were receiving active cancer therapy (chemotherapy, radiotherapy, chemoradiotherapy, or surgery). The most common cancer types were colorectal (30% of participants), head and neck (25%), lung (15%), and gastric/oesophageal (12%). A small number of studies included breast, pancreatic, or prostate cancer patients.

**Setting:** Hospital-based (inpatient or outpatient oncology clinics) across 12 countries (USA, UK, Netherlands, Germany, Brazil, China, Japan, Australia, Canada, France, Italy, Spain). All studies were conducted in academic medical centres or tertiary care hospitals.

**Exclusion criteria (across studies):** Patients with severe renal impairment (creatinine clearance <30 mL/min), hepatic failure, uncontrolled diabetes, or those already receiving enteral or parenteral nutrition were excluded. Most studies also excluded patients with a life expectancy <3 months.

**Baseline characteristics:** Mean age ranged from 52 to 71 years across studies. Approximately 55% were male. Mean BMI at baseline ranged from 21 to 28 kg/m². About 40% of participants were malnourished or at risk of malnutrition at baseline (defined by PG-SGA score ≥4 or weight loss >5% in the prior 3 months). The mean protein intake at baseline was 0.8–1.0 g/kg body weight/day (below the recommended 1.2–1.5 g/kg/day for cancer patients).

**Body weight:** Measured using calibrated digital scales at baseline and at study end (typically 8–12 weeks). Some studies also measured mid-intervention at 4 weeks.

**Lean body mass:** Assessed using dual-energy X-ray absorptiometry (DXA) in 12 studies, bioelectrical impedance analysis (BIA) in 4 studies, and computed tomography (CT) at the L3 vertebral level (skeletal muscle index) in 2 studies. DXA is considered the gold standard for body composition analysis in clinical research; BIA is less precise but more portable.

**Handgrip strength:** Measured using a handheld dynamometer (Jamar or similar). Participants performed 3 trials with their dominant hand, and the maximum value was recorded. Units: kilograms (kg).

**Physical function:** Assessed using the 6-minute walk test (distance walked in 6 minutes, in metres) in 5 studies, and the timed up-and-go test (seconds to stand from a chair, walk 3 metres, turn, and sit back down) in 3 studies.

**Quality of life:** Measured using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30, 0–100 scale, higher = better function) in 8 studies, and the Functional Assessment of Cancer Therapy – General (FACT-G) in 3 studies.

**Nutritional status:** Assessed using the Patient-Generated Subjective Global Assessment (PG-SGA, 0–35 scale, higher = worse nutritional status) in 6 studies.

**Adverse events:** Self-reported gastrointestinal symptoms (nausea, vomiting, diarrhoea, constipation, bloating) using a 4-point Likert scale (none, mild, moderate, severe). Renal function was monitored via serum creatinine and blood urea nitrogen (BUN) in 10 studies.

**Study design:** This was a systematic review and meta-analysis of randomised controlled trials (RCTs). The authors searched 5 databases (PubMed, Embase, Cochrane CENTRAL, CINAHL, and Web of Science) from inception to March 2024. Two independent reviewers screened titles/abstracts and full texts, extracted data, and assessed risk of bias using the Cochrane Risk of Bias 2.0 tool.

**Inclusion criteria for individual studies:** RCTs (parallel-group or crossover) that compared high-protein supplementation (≥20 g/day additional protein) to any control (standard care, placebo, low-protein supplement, or dietary advice) in adults receiving active cancer therapy. Minimum intervention duration: 4 weeks. Studies had to report at least one of the primary outcomes (body weight, lean body mass, handgrip strength).

**Statistical approach:** Random-effects meta-analysis using the DerSimonian and Laird method. This model assumes that the true effect size varies across studies (due to differences in population, intervention, and setting) and produces a more conservative estimate than a fixed-effects model. Results are reported as mean differences (MD) or standardised mean differences (SMD) with 95% confidence intervals (CI). Heterogeneity was assessed using the I² statistic (0–100%, higher = more variability between studies). Publication bias was assessed using funnel plots and Egger's test.

**Subgroup analyses:** The authors pre-specified subgroup analyses by cancer type (colorectal vs. head and neck vs. other), baseline nutritional status (malnourished vs. well-nourished), protein dose (20–30 g/day vs. >30 g/day), intervention duration (4–8 weeks vs. >8 weeks), and supplement type (whey vs. soy vs. mixed).

**Sensitivity analyses:** Leave-one-out analyses (removing one study at a time to check if any single study drove the results) and analyses restricted to studies with low risk of bias.

**What this design can and cannot prove:**

This is a meta-analysis of RCTs, which sits at the top of the evidence hierarchy for intervention effectiveness. Because it pools data from multiple randomised trials, it can provide a more precise estimate of the average treatment effect than any single study. Randomisation in the individual trials minimises confounding (e.g., patients who choose to take protein supplements may also be healthier or more motivated; randomisation balances these factors across groups). Blinding (where used) reduces placebo effects and measurement bias.

However, a meta-analysis inherits the limitations of its constituent studies. If the individual RCTs are small, short, or poorly blinded, the pooled estimate may still be biased. The "apples and oranges" problem also applies: combining studies with different cancer types, different protein doses, different control conditions, and different outcome measures may obscure important subgroup effects. The random-effects model partially addresses this, but it cannot correct for systematic differences in study quality.

This design can prove that high-protein supplementation causes a statistically significant increase in body weight and lean body mass on average across these populations. It cannot prove that every cancer patient will benefit, nor can it determine the optimal dose, timing, or protein source for a specific individual. It also cannot rule out that the observed weight gain is partly due to increased fluid retention (oedema) rather than true muscle gain, as most studies did not measure hydration status.

**Methodological weaknesses of the included studies:**

Only 6 of 18 studies were double-blind (participants and assessors blinded). In the remaining 12, participants and/or researchers knew which group they were in, which could introduce bias (e.g., control participants may have changed their diet, or assessors may have subconsciously favoured the intervention group).

Median intervention duration was 10 weeks (range 4–24 weeks). This may be too short to detect meaningful changes in muscle strength or physical function, which typically require 12–16 weeks of resistance training plus adequate protein.

Compliance with supplementation was reported in only 10 studies. In those that did report it, mean compliance was 72% (range 55–92%), meaning some participants did not consume the full prescribed dose.

Only 5 studies included a resistance exercise component alongside supplementation. Since protein synthesis is stimulated by mechanical loading, the effects of protein alone (without exercise) may be blunted.

Attrition was high in some studies (mean 18%, range 5–35%), often due to disease progression, treatment side effects, or death. This can bias results if dropouts differ systematically between groups.

**Primary outcomes:**

**Body weight (kg):** High-protein supplementation led to a statistically significant increase in body weight compared to control. Mean difference: +1.2 kg (95% CI: 0.6 to 1.8 kg, p = 0.001, I² = 42%). This was consistent across most subgroups, though the effect was larger in malnourished patients (+1.8 kg, 95% CI: 0.9 to 2.7 kg) than in well-nourished patients (+0.5 kg, 95% CI: −0.2 to 1.2 kg).

**Lean body mass (kg):** High-protein supplementation significantly increased lean body mass. Mean difference: +0.8 kg (95% CI: 0.3 to 1.3 kg, p = 0.004, I² = 38%). The effect was larger in studies using DXA (+1.0 kg) compared to BIA (+0.4 kg), and larger in studies with whey protein (+1.1 kg) compared to soy (+0.5 kg) or mixed blends (+0.6 kg).

**Handgrip strength (kg):** No statistically significant difference between groups. Mean difference: +0.4 kg (95% CI: −0.3 to 1.1 kg, p = 0.28, I² = 15%). This null result was consistent across all subgroups.

**Secondary outcomes:**

**Physical function (6-minute walk test):** No significant difference. Mean difference: +12 metres (95% CI: −8 to 32 metres, p = 0.24, I² = 22%). A change of 30–50 metres is considered clinically meaningful in cancer patients.

**Quality of life (EORTC QLQ-C30 global health score):** No significant difference. Mean difference: +2.1 points (95% CI: −1.8 to 6.0 points, p = 0.29, I² = 0%). A change of 10 points is considered clinically meaningful.

**Nutritional status (PG-SGA score):** Significant improvement favouring high-protein supplementation. Mean difference: −1.4 points (95% CI: −2.5 to −0.3 points, p = 0.02, I² = 35%). Lower scores indicate better nutritional status.

**Adverse events:** No significant difference in gastrointestinal symptoms between groups (risk ratio: 1.12, 95% CI: 0.85 to 1.48, p = 0.42). Renal function (serum creatinine, BUN) remained within normal limits in both groups, with no significant between-group differences.

**Subgroup analyses:**

**Cancer type:** The effect on body weight was largest in head and neck cancer patients (+1.6 kg) and smallest in lung cancer patients (+0.6 kg). This may reflect differences in baseline malnutrition rates and treatment intensity.

**Protein dose:** Doses >30 g/day produced slightly larger effects on lean body mass (+1.0 kg) than doses of 20–30 g/day (+0.6 kg), but the difference was not statistically significant (p for interaction = 0.18).

**Intervention duration:** Studies lasting >8 weeks showed larger effects on body weight (+1.5 kg) than those lasting 4–8 weeks (+0.7 kg), suggesting a dose-response relationship with time.

**Supplement type:** Whey protein showed the largest effects on lean body mass (+1.1 kg) compared to soy (+0.5 kg) and mixed blends (+0.6 kg). This may be due to whey's higher leucine content (a key amino acid for muscle protein synthesis).

**Publication bias:** Funnel plot asymmetry was detected for the body weight outcome (Egger's test p = 0.04), suggesting possible publication bias favouring positive results. After adjusting for this using the trim-and-fill method, the effect on body weight remained significant but was reduced to +0.8 kg (95% CI: 0.2 to 1.4 kg).

The average weight gain of 1.2 kg (~2.6 lbs) over 10 weeks is modest but clinically relevant for cancer patients who are losing weight due to their disease and treatment. To put this in perspective: cancer cachexia (unintentional weight loss) affects 50–80% of advanced cancer patients, and a weight loss of >5% over 6 months is associated with poorer survival and quality of life. Gaining 1.2 kg represents a reversal of this trajectory for many patients.

The gain in lean body mass of 0.8 kg (~1.8 lbs) is roughly equivalent to the amount of muscle a healthy young adult might gain from 8–10 weeks of resistance training combined with adequate protein intake. For a cancer patient who is not exercising (most studies did not include exercise), this is a meaningful preservation of muscle tissue that would otherwise be lost.

However, the lack of improvement in handgrip strength (only +0.4 kg, which is less than the weight of a small apple) and physical function (+12 metres on the 6-minute walk test, which is about the length of a school bus) suggests that protein supplementation alone, without resistance exercise, is insufficient to translate increased muscle mass into improved function. This is consistent with the physiology: muscle protein synthesis requires both an amino acid stimulus (protein) and a mechanical stimulus (exercise) to produce functional gains.

The improvement in PG-SGA score (−1.4 points) is modest but clinically meaningful. A change of ≥1 point is considered a minimal clinically important difference in cancer patients. This suggests that protein supplementation improves overall nutritional status, even if it doesn't directly improve strength or quality of life.

**Author-acknowledged limitations:**

High heterogeneity in study designs, populations, interventions, and outcome measures, despite using random-effects models.

Only 6 of 18 studies were double-blind, increasing risk of performance and detection bias.

Median intervention duration of 10 weeks may be insufficient to detect changes in strength and function.

Compliance with supplementation was suboptimal (mean 72%) and not reported in all studies.

Most studies did not control for total energy intake, so the protein group may have consumed more calories overall, confounding the results.

Few studies included resistance exercise, which is known to synergise with protein for muscle gain.

Publication bias was detected for the body weight outcome, suggesting that small negative studies may be missing from